The Stark Realities of Reproducible Sociological Research

Q-Step_Slide

Alternative titles: Some Newer Rules of the Sociological Method or The Moon Under Water


Professor Vernon Gayle, University of Edinburgh, UK.


Please remember that this work is very exploratory.

Positive comments are always appreciated, but brickbats improve work. Here is how to contact me or @profbigvern.


Next Actions:

  1. Share this notebook with colleagues.

License

This work must not be copied or cited without written permision from the author

Copyright (c) 2017 Vernon Gayle, University of Edinburgh

When the work is nearer completion I will make it more open with an

The MIT License (MIT)

which will say...

Copyright (c) 2017 Vernon Gayle, University of Edinburgh

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.


Authorship and Meta Information

Author: Professor Vernon Gayle Orcid id: http://orcid.org/0000-0002-1929-5983

Project: Reproducible Sociological Research

Sub-project: Stratification Conference (Edinburgh) September 2017


Using this Notebook

Using Jupyter notebooks for large-scale social science data analysis in sociology is zygotic.

This is an early example of undertaking a complete analytical workflow within a Jupyter notebook.

As this practice becomes more ubiquitos it is likely that there will be improvements and best practices will become much more evident.

Warning.

Within this Jupyter notebook there has been a lot of non-routine work. For example I have 'swivel-chaired' between data analytical software packages and changed kernels.

It may from time to time be necessary to re-start the notebook depending on how stable your computing environment is.

Therefore in some sections I re-start a R session.

Please remember that this work is very exploratory.

Positive comments are always appreciated, but brickbats improve work. Here is how to contact me or @profbigvern.


Updates

Latest Update: 28th June (pushed up to https://github.com/vernongayle/new_rules_of_the_sociological_method ) and e-mailed to colleagues.

Previous Updates:

27th June (my Mum's birthday) General work 26th June Ethics Approval Form Submitted 25th June Pre-paratory work begins 24th June Pre-Analysis Plan submitted to date stamping


Pre-Analysis Plan

A pre-analysis plan is openly available (in word format) https://github.com/vernongayle/new_rules_of_the_sociological_method/blob/master/pre_analysis_plan_20170624_vg_v1.docx .

The pre-analysis plan has been formally timestamped by Originstamp.

hash: ca0fc7d948fd67cf8a1a2ac9111e9bf40425c010dfdf76ef33a0e578a90981a8

Submitted to OriginStamp: 24 Jun 2017 21:00:24 GMT Submitted to the Blockchain: 25 Jun 2017 16:00:21 GMT

This document can be verifyied using the hash at https://app.originstamp.org/verify .

Note: Some researcher might not consider this document to be a pure pre-analysis plan. This is because I have examined the data and worked with it previously. However, it is an example of how a pre-analysis plan could work in the sociological analysis of an existing large-scale social survey dataset.


Research Ethics Approval Application

A research ethics approval application has been made to the School of Social and Political Science, University of Edinburgh https://github.com/vernongayle/new_rules_of_the_sociological_method/blob/master/Research_Ethics_Form_20170626_vg_v1.pdf .

Research Ethics Approval

From: MOORE Niamh Sent: 26 June 2017 17:01 To: GAYLE Vernon Cc: SSPS Research Subject: FW: Ethics form submission (Vernon Gayle: The Stark Realities of Reproducible Sociological Research)

Hi Vernon,

Approved at level 1. If only they were all so straightforward.

Good luck with the project.

All the best

Niamh

All the best with your application.

Niamh

Dr Niamh Moore

Chancellor's Fellow I Deputy Director of Research (Ethics) Sociology I Room 3.09, 3F2 I 18 Buccleuch Place
School of Social and Political Sciences I University of Edinburgh I Edinburgh EH8 8LN

niamh.moore@ed.ac.uk l @rawfeminism l +44(0)131-6508260 l skype: niamhresearcher http://www.sociology.ed.ac.uk/people/staff/niamh_moore


Research Question

Can a sociological researcher follow Professor Philip Stark's checklist for reproducible research and undertake a plausible piece of analysis, using genuine large-scale data with realistic levels of messiness?


Overview of the Reproducibility Checklist

http://www.bitss.org/2015/12/31/science-is-show-me-not-trust-me/

Philip Stark outlines 14 reproducibility points that an analysis can fail on

  1. If you relied on Microsoft Excel for computations, fail.
  2. If you did not script your analysis, including data cleaning and munging, fail.
  3. If you did not document your code so that others can read and understand it, fail.
  4. If you did not record and report the versions of the software you used (including library dependencies), fail.
  5. If you did not write tests for your code, fail.
  6. If you did not check the code coverage of your tests, fail.
  7. If you used proprietary software that does not have an open-source equivalent without a really good reason, fail.
  8. If you did not report all the analyses you tried (transformations, tests, selections of variables, models, etc.) before arriving at the one you chose to emphasize, fail.
  9. If you did not make your code (including tests) available, fail.
  10. If you did not make your data available (and a law like FERPA or HIPPA doesn’t prevent it), fail.
  11. If you did not record and report the data format, fail.
  12. If there is no open source tool for reading data in that format, fail.
  13. If you did not provide an adequate data dictionary, fail.
  14. If you published in a journal with a paywall and no open-access policy, fail.

Literate Computing

Fernando Perez says

"Literate Computing is the weaving of a narrative directly into a live computation, interleaving text with code and results to construct a complete piece that relies equally on the textual explanations and the computational components, for the goals of communicating results in scientific computing and data analysis" (see http://blog.fperez.org/).

Literate programming is a paradigm introduced by Donald Knuth in which a program is given as an explanation of its logic in a human readable language (e.g. plain English) with snippets traditional source code (or macros) (see https://en.wikipedia.org/wiki/Literate_programming).

A challenge of this current sub-project is simple - can I undertake a plausible piece of analysis, using genuine large-scale data with realistic levels of messiness, that is 'literate' as well as reproducible?


Computing Environment and Software

Computing Environment

Work undertaken using machine surface pro 109.152.252.166 (my public IP address).

Processor: Intel(R) Core™ i5-4300U CPU@ 1.90 GHz 2.50 GHz
Installed memory (RAM): 4.00 GB
System type: 64-bit Operating System, x-64 based processor


Data Analysis Software

R Analysis

The data analysis that will be undertaken in this paper will mainly be undertaken in R.

The decision to use R is motivated by checklist item 7, and it is an attempt to use and open source data analytical software rather than a proprietary software package.

WARNING

You must have R installed on your machine.

You must have installed the R kernel (See https://anaconda.org/r/r-irkernel ).

You must have installed the R libraries foreign and survey

for example run the code install.packages("foreign","survey")

(see https://cran.r-project.org/web/packages/survey/index.html ; https://cran.r-project.org/web/packages/foreign/index.html).

Reminder *Switch Kernel to R < Menu kernel - change kernel>*

Getting the libraries for R

In [1]:
library(foreign)
library(survey)
library(car)
library(dplyr)
library(weights)
library(dummies)
Warning message:
: package 'survey' was built under R version 3.2.5Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Warning message:
: package 'survival' was built under R version 3.2.5
Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

Warning message:
: package 'car' was built under R version 3.2.5Warning message:
: package 'dplyr' was built under R version 3.2.5
Attaching package: 'dplyr'

The following object is masked from 'package:car':

    recode

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Warning message:
: package 'weights' was built under R version 3.2.5Loading required package: Hmisc
Warning message:
: package 'Hmisc' was built under R version 3.2.5Loading required package: lattice
Loading required package: Formula
Warning message:
: package 'Formula' was built under R version 3.2.5Loading required package: ggplot2
Warning message:
: package 'ggplot2' was built under R version 3.2.5
Error: package 'ggplot2' could not be loaded
Warning message:
: package 'dummies' was built under R version 3.2.5dummies-1.5.6 provided by Decision Patterns

Various WARNINGS will appear. Don't panic.

If you have a more serious ERROR message here it is possibly because you have not switched to the _R Kernel_.

The Code Test

Part 1 Logistic Regression

In this block of the work I undertake a test of the software.

Because the analyses below will be based on a logistic regression model I have chosen to check the results of a logit model in my software environment against a known result.

In this section I will import a dataset from the Stata website (www.stata-press.com) and estimate a logit model.

In [3]:
myautodata <- read.dta("http://www.stata-press.com/data/r12/auto.dta")
In [4]:
summary(myautodata)
Out[4]:
     make               price            mpg            rep78      
 Length:74          Min.   : 3291   Min.   :12.00   Min.   :1.000  
 Class :character   1st Qu.: 4220   1st Qu.:18.00   1st Qu.:3.000  
 Mode  :character   Median : 5006   Median :20.00   Median :3.000  
                    Mean   : 6165   Mean   :21.30   Mean   :3.406  
                    3rd Qu.: 6332   3rd Qu.:24.75   3rd Qu.:4.000  
                    Max.   :15906   Max.   :41.00   Max.   :5.000  
                                                    NA's   :5      
    headroom         trunk           weight         length           turn      
 Min.   :1.500   Min.   : 5.00   Min.   :1760   Min.   :142.0   Min.   :31.00  
 1st Qu.:2.500   1st Qu.:10.25   1st Qu.:2250   1st Qu.:170.0   1st Qu.:36.00  
 Median :3.000   Median :14.00   Median :3190   Median :192.5   Median :40.00  
 Mean   :2.993   Mean   :13.76   Mean   :3019   Mean   :187.9   Mean   :39.65  
 3rd Qu.:3.500   3rd Qu.:16.75   3rd Qu.:3600   3rd Qu.:203.8   3rd Qu.:43.00  
 Max.   :5.000   Max.   :23.00   Max.   :4840   Max.   :233.0   Max.   :51.00  
                                                                               
  displacement     gear_ratio        foreign  
 Min.   : 79.0   Min.   :2.190   Domestic:52  
 1st Qu.:119.0   1st Qu.:2.730   Foreign :22  
 Median :196.0   Median :2.955                
 Mean   :197.3   Mean   :3.015                
 3rd Qu.:245.2   3rd Qu.:3.353                
 Max.   :425.0   Max.   :3.890                
                                              

Estimating a logistic regression model.

  • Outcome variable = foreign
  • Explanatory variables = weight + mpg
In [7]:
myautologit1 <- glm(foreign ~ weight + mpg,  data = myautodata, family = "binomial")

Summarizing the output of the logistic regression model.

In [8]:
summary(myautologit1)
Out[8]:
Call:
glm(formula = foreign ~ weight + mpg, family = "binomial", data = myautodata)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.0436  -0.4285  -0.2207   0.5347   2.0679  

Coefficients:
             Estimate Std. Error z value Pr(>|z|)    
(Intercept) 13.708367   4.518709   3.034 0.002416 ** 
weight      -0.003907   0.001012  -3.862 0.000113 ***
mpg         -0.168587   0.091917  -1.834 0.066637 .  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 90.066  on 73  degrees of freedom
Residual deviance: 54.350  on 71  degrees of freedom
AIC: 60.35

Number of Fisher Scoring iterations: 6

These results are identical to the results that are found in the Stata Manual p.1271.

logit_slide

Therefore I am confident that the software environment is providing the correct results for a logistic regression model.

Because I intend to use quasi-variances I will also test analyses below will be based on a logistic regression model I have chosen to check the results of a logit model in my software environment against a known result.

In this section I will import a dataset from the Stata website (www.stata-press.com) and estimate a logit model.


Part II Quasi-Variance Estimation

In the replication part of the analysis I intend to calculate quasi-variance estimates after estimating the logistic regression model. As a furth code test I will use the ship damage data and estimate an overdispersed poisson loglinear model for ship damage data from McCullagh and Nelder (1989), Sec 6.3.2.

_Make sure that in R qvcalc is installed_

code required in R
install.packages('qvcalc')

In [22]:
library(MASS)
library(qvcalc)
data(ships)
ships$year <- as.factor(ships$year)
ships$period <- as.factor(ships$period)
shipmodel <- glm(formula = incidents ~ type + year + period,
    family = quasipoisson, 
    data = ships, subset = (service > 0), offset = log(service))
summary(shipmodel)
shiptype.qvs <- qvcalc(shipmodel, "type")
summary(shiptype.qvs, digits = 4)
plot(shiptype.qvs)
Warning message:
: package 'qvcalc' was built under R version 3.2.5
Out[22]:
Call:
glm(formula = incidents ~ type + year + period, family = quasipoisson, 
    data = ships, subset = (service > 0), offset = log(service))

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.6768  -0.8293  -0.4370   0.5058   2.7912  

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -6.40590    0.28276 -22.655  < 2e-16 ***
typeB       -0.54334    0.23094  -2.353  0.02681 *  
typeC       -0.68740    0.42789  -1.607  0.12072    
typeD       -0.07596    0.37787  -0.201  0.84230    
typeE        0.32558    0.30674   1.061  0.29864    
year65       0.69714    0.19459   3.583  0.00143 ** 
year70       0.81843    0.22077   3.707  0.00105 ** 
year75       0.45343    0.30321   1.495  0.14733    
period75     0.38447    0.15380   2.500  0.01935 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for quasipoisson family taken to be 1.691028)

    Null deviance: 146.328  on 33  degrees of freedom
Residual deviance:  38.695  on 25  degrees of freedom
AIC: NA

Number of Fisher Scoring iterations: 5
Model call:  glm(formula = incidents ~ type + year + period, family = quasipoisson,      data = ships, subset = (service > 0), offset = log(service)) 
Factor name:  type 
      estimate     SE quasiSE quasiVar
    A  0.00000 0.0000  0.2010  0.04039
    B -0.54334 0.2309  0.1127  0.01270
    C -0.68740 0.4279  0.3753  0.14081
    D -0.07596 0.3779  0.3239  0.10491
    E  0.32558 0.3067  0.2322  0.05390
Worst relative errors in SEs of simple contrasts (%):  -0.7 0.9 
Worst relative errors over *all* contrasts (%):  -2.1 1.6 

These results are identical to the results that are found in Firth, D. and De Menezes, R.X., 2004. Quasi-variances. Biometrika, pp.65-80.

logit_slide

Therefore I am confident that the software environment is providing the correct results for quasi-variance estimates.


The Research Dataset

The Youth Cohort Study of England and Wales (YCS)

The Youth Cohort Study of England and Wales (YCS) is a major longitudinal study that began in the mid-1980s. It is a large-scale nationally representative survey funded by the government and is designed to monitor the behaviour of young people as they reach the minimum school leaving age and either remain in education or enter the labour market.

There are a number of challenges associated with analysing YCS data, most notably inadequate documentation of the procedures used to construct the data-sets.

YCS Cohort Nine (1998-2000) UK Data Archive Study 4009

https://discover.ukdataservice.ac.uk/catalogue/?sn=4009

The population studied was male and female school pupils in England and Wales who had reached minimum school leaving age in the 1996/1997 school year. To be eligible for inclusion they had to be aged 16 on August 31st 1997.

Downloaded: UK Data Service https://www.ukdataservice.ac.uk/
Date: 19th June 2017
Time: 19:54

Finch, S.A., La Valle, I., McAleese, I., Russell, N., Nice, D., Fitzgerald, R., Finch, S.A. (2004). Youth Cohort Study of England and Wales, 1998-2000. [data collection]. 5th Edition. UK Data Service. SN: 4009, http://doi.org/10.5255/UKDA-SN-4009-1


Data Enabling (a real attempt with the raw data)

Description of the dataset

The dataset used in this set of analyses is from YCS cohort 9 - sweep 1.

The file is called "ycs9sw1".

The file will be read in Stata format (i.e. th ycs9sw1.dta).

Data Wrangling (a real attempt with the raw data)

In [1]:
# If you have not run the notebook sequentially... 

# theses libraries are required

library(foreign)
library(survey)
library(car)
library(dplyr)
library(weights)
library(dummies)
Warning message:
: package 'survey' was built under R version 3.2.5Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Warning message:
: package 'survival' was built under R version 3.2.5
Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

Warning message:
: package 'car' was built under R version 3.2.5Warning message:
: package 'dplyr' was built under R version 3.2.5
Attaching package: 'dplyr'

The following object is masked from 'package:car':

    recode

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Warning message:
: package 'weights' was built under R version 3.2.5Loading required package: Hmisc
Warning message:
: package 'Hmisc' was built under R version 3.2.5Loading required package: lattice
Loading required package: Formula
Warning message:
: package 'Formula' was built under R version 3.2.5Loading required package: ggplot2
Warning message:
: package 'ggplot2' was built under R version 3.2.5
Error: package 'ggplot2' could not be loaded
Warning message:
: package 'dummies' was built under R version 3.2.5dummies-1.5.6 provided by Decision Patterns

Various WARNINGS will appear. Don't panic!


This file is located on (my) OneDrive.

An internet connection is useful but it is not required, as the dataset is stored locally.

When reading your version of the data from your specific location....
Remember that C:/temp/ (is windows) is C:/data/ here in the Jupyter notebook.

In [10]:
# This file is located on (my) OneDrive.

mydata.df <- read.dta("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/UKDA-4009-stata8/stata8/ycs9sw1.dta")
Warning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecated

Various WARNINGS will appear. Don't panic!

These error messages occur because R is reading a Stata .dta file. It is a genuine large-scale research dataset and includes a large number of value labels and variable labels.


In [3]:
summary(mydata.df)
Warning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecatedWarning message:
In `levels<-`(`*tmp*`, value = if (nl == nL) as.character(labels) else paste0(labels, : duplicated levels in factors are deprecated
Out[3]:
     serial           weight              s1estab               s1gor     
 Min.   :200001   Min.   :0.6025   lea comp 18:6207   south east   :2365  
 1st Qu.:206123   1st Qu.:0.7661   lea comp 16:4179   eastern      :1608  
 Median :211589   Median :0.8779   gm  comp 18:1617   west midlands:1595  
 Mean   :212056   Mean   :1.0000   independent:1053   london       :1572  
 3rd Qu.:217027   3rd Qu.:1.0576   gm  comp 16: 536   north west   :1506  
 Max.   :231392   Max.   :2.5176   modern     : 454   south west   :1423  
                                   (Other)    : 616   (Other)      :4593  
                  sex      
 not answered (9)   :   0  
 item not applicable:   0  
 male               :6889  
 female             :7773  
                           
                           
                           
                                                s1resp    
 not answered (99)                                 :   0  
 item not applicable                               :   0  
 postal mailout 1                                  :9311  
 postal mailout 3                                  :2564  
 postal mailout 4                                  :1299  
 questionnaire sent in response to telephone chaser:  34  
 telephone interview                               :1454  
                  a1_a                        a1_b     
 not answered (9)   :    0   not answered (9)   :   0  
 item not applicable:    0   item not applicable:   0  
 agree              :10065   agree              :4787  
 disagree           : 4166   disagree           :9369  
 NA's               :  431   NA's               : 506  
                                                       
                                                       
                  a1_c                       a1_d      
 not answered (9)   :   0   not answered (9)   :    0  
 item not applicable:   0   item not applicable:    0  
 agree              :9875   agree              :12124  
 disagree           :4267   disagree           : 2074  
 NA's               : 520   NA's               :  464  
                                                       
                                                       
                  a2_1                        a2_2      
 not answered (9)   :    0   not answered (9)   :    0  
 item not applicable:    0   item not applicable:    0  
 yes                :13837   yes                :13393  
 no                 :  732   no                 :  413  
 NA's               :   93   NA's               :  856  
                                                        
                                                        
                  a2_3                       a3_1      
 not answered (9)   :   0   not answered (9)   :    0  
 item not applicable:   0   item not applicable:    0  
 a great deal       :2714   yes                :12868  
 quite a lot        :7236   no                 : 1413  
 not much           :3018   not sure           :  289  
 nothing at all     : 405   NA's               :   92  
 NA's               :1289                              
                 a3_1a                      a3_1b     
 not answered (9)   :   0   not answered (9)   :   0  
 item not applicable:   0   item not applicable:   0  
 yes                :9193   yes                :6325  
 no                 :3623   no                 :6448  
 NA's               :1846   NA's               :1889  
                                                      
                                                      
                  a4_1                        a4_2      
 not answered (9)   :    0   not answered (9)   :    0  
 item not applicable:    0   item not applicable:    0  
 yes                :13961   yes                :13305  
 no                 :  623   no                 :  633  
 NA's               :   78   NA's               :  724  
                                                        
                                                        
                 a4_3a                       a4_3b      
 not answered (9)   :    0   not answered (9)   :    0  
 item not applicable:    0   item not applicable:    0  
 yes                :11147   yes                :11131  
 no                 : 2059   no                 : 2103  
 NA's               : 1456   NA's               : 1428  
                                                        
                                                        
                 a4_3c                       a5_1     
 not answered (9)   :   0   not answered (9)   :   0  
 item not applicable:   0   item not applicable:   0  
 yes                :6281   yes                :8829  
 no                 :6892   no                 :5036  
 NA's               :1489   NA's               : 797  
                                                      
                                                      
                 a5_2a                      a5_2b     
 not answered (9)   :   0   not answered (9)   :   0  
 item not applicable:   0   item not applicable:   0  
 yes                :7244   yes                :7152  
 no                 :1531   no                 :1611  
 NA's               :5887   NA's               :5899  
                                                      
                                                      
                 a5_2c                      a6_1a      
 not answered (9)   :   0   not answered (9)   :    0  
 item not applicable:   0   item not applicable:    0  
 yes                :3606   yes                :12548  
 no                 :5117   no                 : 1969  
 NA's               :5939   NA's               :  145  
                                                       
                                                       
                 a6_1b                        a7      
 not answered (9)   :   0   not answered (9)   :   0  
 item not applicable:   0   item not applicable:   0  
 very               : 888   yes                :9318  
 fairly             :6904   to some extent     :3975  
 not very           :3856   no                 :1257  
 not all            : 879   NA's               : 112  
 NA's               :2135                             
                   a8      
 not answered (9)   :   0  
 item not applicable:   0  
 very easy          :2684  
 fairly easy        :7730  
 fairly difficult   :3380  
 very difficult     : 698  
 NA's               : 170  
                                                           a9_1      
 full-time education at school or a college of further educat:10901  
 modern apprenticeship, national traineeship or other governm: 1320  
 full-time job (over 30 hours a week)                        : 1253  
 out of work, unemployed                                     :  617  
 part-time job (if this is your main activity)               :  339  
 (Other)                                                     :  183  
 NA's                                                        :   49  
                                                          a9_21      
 pregnancy/looking after children/family                     :   56  
 waiting to start a new job/government supported training/tra:   40  
 part-time education                                         :   32  
 other                                                       :   20  
 illness/accident                                            :   11  
 (Other)                                                     :   17  
 NA's                                                        :14486  
                                                          a9_22      
 temporary/casual work                                       :    2  
 waiting to start a new job/government supported training/tra:    2  
 pregnancy/looking after children/family                     :    1  
 holiday (school, college, university)                       :    1  
 not answered (99)                                           :    0  
 (Other)                                                     :    0  
 NA's                                                        :14656  
                                     a9_23          a11_1a         
 not answered (99)                      :    0   Length:14662      
 item not applicable                    :    0   Class :character  
 part-time education                    :    0   Mode  :character  
 pregnancy/looking after children/family:    0                     
 temporary/casual work                  :    0                     
 (Other)                                :    0                     
 NA's                                   :14662                     
    a11_1b             a11_1c             a11_2a             a11_2b         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a11_2c             a11_3a             a11_3b             a11_3c         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a11_4a             a11_4b             a11_4c             a11_5a         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a11_5b             a11_5c             a11_6a             a11_6b         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a11_6c             a11_7a             a11_7b             a11_7c         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a11_8a             a11_8b             a11_8c             a11_9a         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a11_9b             a11_9c            a11_10a            a11_10b         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
   a11_10c            a11_11a            a11_11b            a11_11c         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
   a11_11d                                            a11oga1    
 Length:14662       sport/physical education studies      :1252  
 Class :character   drama                                 :1141  
 Mode  :character   religious studies  (includes theology):1057  
                    music                                 : 693  
                    information technology/info systems   : 671  
                    (Other)                               :6138  
                    NA's                                  :3710  
                                   a11oga2    
 religious studies  (includes theology): 750  
 chemistry                             : 471  
 sport/physical education studies      : 446  
 drama                                 : 442  
 information technology/info systems   : 373  
 (Other)                               :3792  
 NA's                                  :8388  
                                   a11oga3     
 physics                               :  435  
 biology                               :  314  
 religious studies  (includes theology):  297  
 chemistry                             :  259  
 science/single award                  :  200  
 (Other)                               : 1438  
 NA's                                  :11719  
                                   a11oga4     
 religious studies  (includes theology):  174  
 physics                               :  113  
 chemistry                             :   89  
 biology                               :   88  
 science/single award                  :   75  
 (Other)                               :  662  
 NA's                                  :13461  
                                   a11oga5     
 religious studies  (includes theology):   80  
 physics                               :   35  
 information technology/info systems   :   34  
 chemistry                             :   30  
 biology                               :   25  
 (Other)                               :  233  
 NA's                                  :14225  
                                   a11oga6     
 physics                               :    6  
 religious studies  (includes theology):    6  
 chemistry                             :    5  
 science/single award                  :    3  
 statistics                            :    3  
 (Other)                               :   17  
 NA's                                  :14622  
                                   a11oga7     
 science in society                    :    2  
 biology                               :    1  
 mathematics (further)                 :    1  
 religious studies  (includes theology):    1  
 welsh literature                      :    1  
 (Other)                               :    0  
 NA's                                  :14656  
                                             a11oga8     
 stage and performing arts dual award (1st grade):    2  
 item not applicable                             :    0  
 biology                                         :    0  
 biology/human                                   :    0  
 biology/ social                                 :    0  
 (Other)                                         :    0  
 NA's                                            :14660  
                     a11oga9                                        a11ogb1    
 item not applicable     :    0   sport/physical education studies      :1252  
 biology                 :    0   drama                                 :1141  
 biology/human           :    0   religious studies  (includes theology):1057  
 biology/ social         :    0   music                                 : 693  
 biology/human and social:    0   information technology/info systems   : 671  
 (Other)                 :    0   (Other)                               :6138  
 NA's                    :14662   NA's                                  :3710  
                                   a11ogb2    
 religious studies  (includes theology): 750  
 chemistry                             : 471  
 sport/physical education studies      : 446  
 drama                                 : 442  
 information technology/info systems   : 373  
 (Other)                               :3792  
 NA's                                  :8388  
                                   a11ogb3     
 physics                               :  435  
 biology                               :  314  
 religious studies  (includes theology):  297  
 chemistry                             :  259  
 science/single award                  :  200  
 (Other)                               : 1438  
 NA's                                  :11719  
                                   a11ogb4     
 religious studies  (includes theology):  174  
 physics                               :  113  
 chemistry                             :   89  
 biology                               :   88  
 science/single award                  :   75  
 (Other)                               :  662  
 NA's                                  :13461  
                                   a11ogb5     
 religious studies  (includes theology):   80  
 physics                               :   35  
 information technology/info systems   :   34  
 chemistry                             :   30  
 biology                               :   25  
 (Other)                               :  233  
 NA's                                  :14225  
                                   a11ogb6     
 physics                               :    6  
 religious studies  (includes theology):    6  
 chemistry                             :    5  
 science/single award                  :    3  
 statistics                            :    3  
 (Other)                               :   17  
 NA's                                  :14622  
                                   a11ogb7     
 science in society                    :    2  
 biology                               :    1  
 mathematics (further)                 :    1  
 religious studies  (includes theology):    1  
 welsh literature                      :    1  
 (Other)                               :    0  
 NA's                                  :14656  
                                             a11ogb8     
 stage and performing arts dual award (1st grade):    2  
 item not applicable                             :    0  
 biology                                         :    0  
 biology/human                                   :    0  
 biology/ social                                 :    0  
 (Other)                                         :    0  
 NA's                                            :14660  
                     a11ogb9        a11ogc1            a11ogc2         
 item not applicable     :    0   Length:14662       Length:14662      
 biology                 :    0   Class :character   Class :character  
 biology/human           :    0   Mode  :character   Mode  :character  
 biology/ social         :    0                                        
 biology/human and social:    0                                        
 (Other)                 :    0                                        
 NA's                    :14662                                        
   a11ogc3            a11ogc4            a11ogc5            a11ogc6         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
   a11ogc7            a11ogc8            a11ogc9         
 Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character  
                                                         
                                                         
                                                         
                                                         
                                a11oq1     
 rsa nvq level 1/certificate       :  214  
 rsa don't know nvq level/other rsa:  126  
 gnvq foundation                   :  116  
 gnvq intermediate                 :  104  
 other qual, bands unclear         :   77  
 (Other)                           :  764  
 NA's                              :13261  
                                         a11oq2     
 rsa nvq level 1/certificate                :   37  
 rsa nvq level 2/diploma                    :   37  
 rsa don't know nvq level/other rsa         :   34  
 other qual, bands unclear                  :   18  
 other band c n.e.c. at nvq level not stated:   13  
 (Other)                                    :  118  
 NA's                                       :14405  
                                         a11oq3     
 rsa don't know nvq level/other rsa         :   13  
 rsa nvq level 1/certificate                :   10  
 other band c n.e.c. at nvq level not stated:    7  
 rsa nvq level 2/diploma                    :    6  
 other qual, bands unclear                  :    6  
 (Other)                                    :   27  
 NA's                                       :14593  
                                         a11oq4     
 other band c n.e.c. at nvq level not stated:    2  
 rsa nvq level 2/diploma                    :    1  
 rsa don't know nvq level/other rsa         :    1  
 city & guilds nvq level 1/part 1           :    1  
 item not applicable                        :    0  
 (Other)                                    :    0  
 NA's                                       :14657  
                                a11oq5                      a11oq6     
 rsa don't know nvq level/other rsa:    1   item not applicable:    0  
 item not applicable               :    0   gcse               :    0  
 gcse                              :    0   gcse (short course):    0  
 gcse (short course)               :    0   ncc                :    0  
 ncc                               :    0   a-level            :    0  
 (Other)                           :    0   (Other)            :    0  
 NA's                              :14661   NA's               :14662  
                 a11oq7                      a11oq8     
 item not applicable:    0   item not applicable:    0  
 gcse               :    0   gcse               :    0  
 gcse (short course):    0   gcse (short course):    0  
 ncc                :    0   ncc                :    0  
 a-level            :    0   a-level            :    0  
 (Other)            :    0   (Other)            :    0  
 NA's               :14662   NA's               :14662  
                 a11oq9     
 item not applicable:    0  
 gcse               :    0  
 gcse (short course):    0  
 ncc                :    0  
 a-level            :    0  
 (Other)            :    0  
 NA's               :14662  
                                            a11os1     
 information technology & computer applications:  241  
 office and secretarial skills                 :  155  
 business                                      :  103  
 health & social care                          :  102  
 other combined or general courses             :   74  
 (Other)                                       :  726  
 NA's                                          :13261  
                                            a11os2     
 office and secretarial skills                 :   56  
 information technology & computer applications:   42  
 mathematics                                   :   13  
 languages & language studies                  :   12  
 business & management (general)               :    8  
 (Other)                                       :  126  
 NA's                                          :14405  
                                            a11os3     
 information technology & computer applications:   13  
 office and secretarial skills                 :   11  
 languages & language studies                  :    6  
 religious studies                             :    3  
 travel & tourism                              :    3  
 (Other)                                       :   33  
 NA's                                          :14593  
                                                          a11os4     
 communication & mass media                                  :    1  
 science & technology (general)                              :    1  
 information technology & computer applications              :    1  
 not stated                                                  :    1  
 other - includes child development, hairdressing and beauty :    1  
 (Other)                                                     :    0  
 NA's                                                        :14657  
                 a11os5                           a11os6     
 not stated         :    1   item not applicable     :    0  
 item not applicable:    0   biology                 :    0  
 biology            :    0   biology/human           :    0  
 biology/human      :    0   biology/social          :    0  
 biology/social     :    0   biology/human and social:    0  
 (Other)            :    0   (Other)                 :    0  
 NA's               :14661   NA's                    :14662  
                      a11os7                           a11os8     
 item not applicable     :    0   item not applicable     :    0  
 biology                 :    0   biology                 :    0  
 biology/human           :    0   biology/human           :    0  
 biology/social          :    0   biology/social          :    0  
 biology/human and social:    0   biology/human and social:    0  
 (Other)                 :    0   (Other)                 :    0  
 NA's                    :14662   NA's                    :14662  
                      a11os9         a11or1             a11or2         
 item not applicable     :    0   Length:14662       Length:14662      
 biology                 :    0   Class :character   Class :character  
 biology/human           :    0   Mode  :character   Mode  :character  
 biology/social          :    0                                        
 biology/human and social:    0                                        
 (Other)                 :    0                                        
 NA's                    :14662                                        
    a11or3             a11or4             a11or5             a11or6         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a11or7             a11or8             a11or9         
 Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character  
                                                         
                                                         
                                                         
                                                         
                  a12a                                    a12bs1     
 not answered (9)   :    0   mathematics                     :  279  
 item not applicable:    0   english                         :  211  
 yes                : 1109   english literature              :   12  
 no                 :11861   science/double award (1st grade):   10  
 NA's               : 1692   science/single award            :    5  
                             (Other)                         :   66  
                             NA's                            :14079  
                              a12bs2                       a12bs3     
 mathematics                     :   27   science/single award:    9  
 english                         :   21   mathematics         :    9  
 english literature              :   10   english literature  :    7  
 science/single award            :    6   english             :    5  
 science/double award (1st grade):    6   geography           :    4  
 (Other)                         :   27   (Other)             :   24  
 NA's                            :14565   NA's                :14604  
                                  a12bs4     
 english                             :    6  
 art and design                      :    4  
 science/single award                :    2  
 home economics/food  food technology:    2  
 art (without 'design' element)      :    2  
 (Other)                             :   20  
 NA's                                :14626  
                                    a12bs5                       a12bs6     
 mathematics                           :    2   science/single award:    1  
 business studies                      :    1   mathematics         :    1  
 history                               :    1   geography           :    1  
 religious studies  (includes theology):    1   other languages     :    1  
 english                               :    1   item not applicable :    0  
 (Other)                               :    0   (Other)             :    0  
 NA's                                  :14656   NA's                :14658  
                             a12bs7         a12br1             a12br2         
 science/single award           :    1   Length:14662       Length:14662      
 cdt/textiles (include textiles):    1   Class :character   Class :character  
 item not applicable            :    0   Mode  :character   Mode  :character  
 biology                        :    0                                        
 biology/human                  :    0                                        
 (Other)                        :    0                                        
 NA's                           :14660                                        
    a12br3             a12br4             a12br5             a12br6         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
    a12br7                          a12bx      
 Length:14662       not answered (9)   :    0  
 Class :character   item not applicable:    0  
 Mode  :character   NA's               :14662  
                                               
                                               
                                               
                                               
                                                          a12oq1     
 nvq (not rsa, btec or c & g) level 2                        :  111  
 nvq (not rsa, btec or c & g) level 1                        :   52  
 gnvq intermediate                                           :   46  
 other qualification: band not known, i.e. all other courses :   32  
 gce a-level                                                 :   29  
 (Other)                                                     :  274  
 NA's                                                        :14118  
                                                          a12oq2     
 nvq (not rsa, btec or c & g) level 2                        :   21  
 rsa nvq level 1/certificate                                 :   10  
 other qualification: band not known, i.e. all other courses :   10  
 gce a-level                                                 :    9  
 nvq (not rsa, btec or c & g) level 3                        :    9  
 (Other)                                                     :   52  
 NA's                                                        :14551  
                                  a12oq3     
 nvq (not rsa, btec or c & g) level 1:    5  
 rsa nvq level 1/certificate         :    4  
 gce a-level                         :    2  
 nvq (not rsa, btec or c & g) level 3:    2  
 gnvq intermediate                   :    1  
 (Other)                             :    7  
 NA's                                :14641  
                                  a12oq4     
 gce a-level                         :    1  
 nvq (not rsa, btec or c & g) level 2:    1  
 other band c n.e.c. at nvq level 3  :    1  
 item not applicable                 :    0  
 gcse                                :    0  
 (Other)                             :    0  
 NA's                                :14659  
                                   a12oq5     
 other band c n.e.c. at nvq level 3   :    1  
 item not applicable                  :    0  
 gcse                                 :    0  
 gcse short course (specific mentions):    0  
 ncc (national curriculum certificate):    0  
 (Other)                              :    0  
 NA's                                 :14661  
                                   a12oq6     
 other band c n.e.c. at nvq level 3   :    1  
 item not applicable                  :    0  
 gcse                                 :    0  
 gcse short course (specific mentions):    0  
 ncc (national curriculum certificate):    0  
 (Other)                              :    0  
 NA's                                 :14661  
                                            a12os1     
 information technology & computer applications:  108  
 business & management (general)               :   45  
 business                                      :   33  
 office and secretarial skills                 :   31  
 health & social care                          :   22  
 (Other)                                       :  330  
 NA's                                          :14093  
                                            a12os2     
 information technology & computer applications:   27  
 office and secretarial skills                 :   13  
 business & management (general)               :    9  
 hotel & commercial catering                   :    4  
 mathematics                                   :    3  
 (Other)                                       :   56  
 NA's                                          :14550  
                                            a12os3     
 information technology & computer applications:    3  
 office and secretarial skills                 :    2  
 hotel & commercial catering                   :    2  
 biology/human                                 :    1  
 chemistry                                     :    1  
 (Other)                                       :   12  
 NA's                                          :14641  
                                      a12os4                      a12os5     
 religious studies (includes theology)   :    1   not stated         :    1  
 health (general) & health administration:    1   not answered (999) :    0  
 not stated                              :    1   item not applicable:    0  
 not answered (999)                      :    0   biology            :    0  
 item not applicable                     :    0   biology/human      :    0  
 (Other)                                 :    0   (Other)            :    0  
 NA's                                    :14659   NA's               :14661  
                 a12os6         a12or1             a12or2         
 not stated         :    1   Length:14662       Length:14662      
 not answered (999) :    0   Class :character   Class :character  
 item not applicable:    0   Mode  :character   Mode  :character  
 biology            :    0                                        
 biology/human      :    0                                        
 (Other)            :    0                                        
 NA's               :14661                                        
    a12or3             a12or4             a12or5             a12or6         
 Length:14662       Length:14662       Length:14662       Length:14662      
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  
                                                                            
                                                                            
                                                                            
                                                                            
                 a12ox                        a13a      
 not answered (9)   :    0   not answered (9)   :    0  
 item not applicable:    0   item not applicable:    0  
 NA's               :14662   yes                : 1911  
                             no                 :11210  
                             NA's               : 1541  
                                                        
                                                        
                                  a13bq1     
 gce a-level                         :  819  
 gcse                                :  280  
 nvq (not rsa, btec or c & g) level 2:  101  
 gnvq intermediate                   :   97  
 other gnvq (not codes 08-12)        :   87  
 (Other)                             :  480  
 NA's                                :12798  
                                  a13bq2     
 gce a-level                         :  304  
 gcse                                :   66  
 nvq (not rsa, btec or c & g) level 2:   15  
 nvq (not rsa, btec or c & g) level 3:    8  
 gce a/s exam                        :    7  
 (Other)                             :   41  
 NA's                                :14221  
                          a13bq3     
 gce a-level                 :  195  
 gcse                        :   40  
 other gnvq (not codes 08-12):    3  
 gce a/s exam                :    2  
 gnvq advanced               :    2  
 (Other)                     :   13  
 NA's                        :14407  
                                            a13bq4     
 gcse                                          :   17  
 gce a-level                                   :   14  
 gce a/s exam                                  :    2  
 rsa nvq level 1/certificate                   :    1  
 city & guilds don't know nvq level/other c & g:    1  
 (Other)                                       :    1  
 NA's                                          :14626  
                                   a13bq5     
 schedule not obtained                :    0  
 schedule not applicable              :    0  
 item not applicable                  :    0  
 gcse                                 :    0  
 gcse short course (specific mentions):    0  
 (Other)                              :    0  
 NA's                                 :14662  
                                   a13bq6     
 gcse                                 :    1  
 item not applicable                  :    0  
 gcse short course (specific mentions):    0  
 ncc (national curriculum certificate):    0  
 gce a-level                          :    0  
 (Other)                              :    0  
 NA's                                 :14661  
                                                          a13bs1     
 mathematics                                                 :  171  
 business                                                    :   81  
 english                                                     :   77  
 biology                                                     :   68  
 other includes child development, hairdressing and beauty ca:   67  
 (Other)                                                     : 1447  
 NA's                                                        :12751  
                a13bs2                   a13bs3                  a13bs4     
 mathematics       :   33   mathematics     :   22   mathematics    :    4  
 english           :   29   sociology       :   20   general studies:    4  
 biology           :   22   business studies:   13   history        :    3  
 geography         :   22   geography       :   13   law            :    2  
 english literature:   22   english         :   13   psychology     :    2  
 (Other)           :  324   (Other)         :  176   (Other)        :   22  
 NA's              :14210   NA's            :14405   NA's           :14625  
                a13bs5                                    a13bs6     
 physics           :    1   science: double award (1st grade):    1  
 business studies  :    1   item not applicable              :    0  
 art and design    :    1   biology                          :    0  
 sociology         :    1   biology: human                   :    0  
 english literature:    1   biology: social                  :    0  
 (Other)           :    4   (Other)                          :    0  
 NA's              :14653   NA's                             :14661  
                  a13c      
 not answered (9)   :    0  
 item not applicable:    0  
 yes                :  944  
 no                 :  945  
 NA's               :12773  
                            
                            
                                          a13d      
 college of further education (state system):  390  
 sixth form college (state system)          :  219  
 state school (including grant maintained)  :  141  
 training centre                            :  102  
 independent/other college                  :   49  
 (Other)                                    :   13  
 NA's                                       :13748  
                 a14_1                       a14_2      
 not answered (9)   :    0   not answered (9)   :    0  
 item not applicable:    0   item not applicable:    0  
 yes                :11053   yes                :10773  
 no                 : 3465   no                 :  205  
 NA's               :  144   NA's               : 3684  
                                                        
                                                        
                 a15_1          a15_2          a15_21          a15_22     
 not answered (9)   :   0   Min.   :1      Min.   :0.000   Min.   :0.000  
 item not applicable:   0   1st Qu.:1      1st Qu.:0.000   1st Qu.:0.000  
 yes                :5388   Median :1      Median :0.000   Median :0.000  
 no                 :5618   Mean   :1      Mean   :0.045   Mean   :0.021  
 NA's               :3656   3rd Qu.:1      3rd Qu.:0.000   3rd Qu.:0.000  
                            Max.   :1      Max.   :1.000   Max.   :1.000  
                            NA's   :9289   NA's   :9289    NA's   :9289   
     a15_23          a15_24          a15_25         a15_26           a16       
 Min.   :0.000   Min.   :0.000   Min.   :0.00   Min.   :0.000   Min.   : 1.00  
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.00   1st Qu.:0.000   1st Qu.:16.00  
 Median :0.000   Median :1.000   Median :0.00   Median :0.000   Median :20.00  
 Mean   :0.301   Mean   :0.595   Mean   :0.02   Mean   :0.018   Mean   :21.09  
 3rd Qu.:1.000   3rd Qu.:1.000   3rd Qu.:0.00   3rd Qu.:0.000   3rd Qu.:25.00  
 Max.   :1.000   Max.   :1.000   Max.   :1.00   Max.   :1.000   Max.   :50.00  
 NA's   :9289    NA's   :9289    NA's   :9289   NA's   :9289    NA's   :4162   
                  a17                       a18_1          a18_2a      
 not answered (9)   :   0   not answered (9)   :   0   Min.   :   5.0  
 item not applicable:   0   item not applicable:   0   1st Qu.: 130.0  
 yes                :4848   yes                : 803   Median : 180.0  
 no                 :4137   no                 :9999   Mean   : 286.5  
 not sure           :1976   NA's               :3860   3rd Qu.: 400.0  
 NA's               :3701                              Max.   :3000.0  
                                                       NA's   :13939   
                 a18_2b             a19_1             a20_1     
 not answered (9)   :    0   sep       :9948   jun       :5042  
 item not applicable:    0   aug       : 363   jul       :3189  
 term               :  435   dk/na date: 267   may       :1029  
 year               :  298   oct       : 147   don't know: 577  
 other period       :   11   jul       :  73   2000      : 282  
 NA's               :13918   (Other)   : 255   (Other)   : 934  
                             NA's      :3609   NA's      :3609  
                 a21_1      
 not answered (9)   :    0  
 item not applicable:    0  
 yes                :  868  
 no                 :12737  
 NA's               : 1057  
                            
                            
                                         a21_2a     
 college of further education (state system):  576  
 somewhere else                             :   86  
 work                                       :   52  
 training centre run by your employer       :   48  
 private training centre                    :   41  
 (Other)                                    :   56  
 NA's                                       :13803  
                                                     a21_2b     
 there are no course fees to pay                        :  232  
 my parents/family/me                                   :  208  
 it is paid for some other way                          :  166  
 my employer                                            :  163  
 it is paid for using a training voucher or plastic card:   55  
 (Other)                                                :    0  
 NA's                                                   :13838  
                  a22                      a22gcse    
 not answered (9)   :   0   not answered (9)   :   0  
 item not applicable:   0   item not applicable:   0  
 yes                :8008   yes                :2026  
 no                 :6282   no                 :5243  
 NA's               : 372   NA's               :7393  
                                                      
                                                      
                              a22a1                      a22a2      
 mathematics                     :  755   mathematics       :  176  
 english                         :  516   english           :  153  
 spanish                         :   72   english literature:   33  
 general studies                 :   60   sociology         :   24  
 sport/physical education studies:   41   biology           :   13  
 (Other)                         :  582   (Other)           :  207  
 NA's                            :12636   NA's              :14056  
                  a22a3                                       a22a4      
 mathematics         :   54   mathematics                        :   15  
 science/single award:   24   information technology/info systems:   14  
 english             :   18   sociology                          :   14  
 biology             :   16   english                            :   14  
 sociology           :   11   biology                            :   12  
 (Other)             :  157   (Other)                            :  113  
 NA's                :14382   NA's                               :14480  
              a22a5                        a22a6      
 mathematics     :   10   mathematics         :    4  
 english         :   10   geography           :    3  
 biology         :    5   english             :    3  
 sociology       :    5   chemistry           :    2  
 business studies:    4   science/single award:    2  
 (Other)         :   57   (Other)             :   19  
 NA's            :14571   NA's                :14629  
                 a22as                                         a22b1      
 not answered (9)   :   0   general studies                       :  144  
 item not applicable:   0   mathematics                           :   73  
 yes                : 788   mathematics (further)                 :   41  
 no                 :6230   religious studies  (includes theology):   40  
 NA's               :7644   french                                :   37  
                            (Other)                               :  453  
                            NA's                                  :13874  
                                    a22b2      
 general studies                       :   14  
 statistics                            :   10  
 religious studies  (includes theology):    7  
 computer studies/computing            :    6  
 sociology                             :    6  
 (Other)                               :   64  
 NA's                                  :14555  
                               a22b3      
 mathematics (pure and statistics):    2  
 music                            :    2  
 general studies                  :    2  
 biology                          :    1  
 science/single award             :    1  
 (Other)                          :    8  
 NA's                             :14646  
                                 a22b4                       a22b5      
 information technology/info systems:    1   history            :    1  
 geography                          :    1   not answered (999) :    0  
 not answered (999)                 :    0   item not applicable:    0  
 item not applicable                :    0   biology            :    0  
 biology                            :    0   biology/human      :    0  
 (Other)                            :    0   (Other)            :    0  
 NA's                               :14660   NA's               :14661  
                 a22b6                      a22alev    
 not answered (999) :    0   not answered (9)   :   0  
 item not applicable:    0   item not applicable:   0  
 biology            :    0   yes                :6939  
 biology/human      :    0   no                 : 882  
 biology/social     :    0   NA's               :6841  
 (Other)            :    0                             
 NA's               :14662                             
                a22c1                     a22c2                     a22c3     
 mathematics       : 874   chemistry         : 577   geography         : 420  
 biology           : 692   biology           : 521   mathematics       : 400  
 english literature: 577   physics           : 448   biology           : 340  
 geography         : 444   geography         : 426   english literature: 337  
 chemistry         : 370   english literature: 414   physics           : 290  
 (Other)           :3982   (Other)           :4193   (Other)           :4151  
 NA's              :7723   NA's              :8083   NA's              :8724  
                   a22c4                                  a22c5      
 general studies      :  576   general studies               :   47  
 chemistry            :   57   mathematics (further)         :    4  
 mathematics (further):   50   art (without 'design' element):    2  
 physics              :   36   biology                       :    1  
 biology              :   30   physics                       :    1  
 (Other)              :  436   (Other)                       :   11  
 NA's                 :13477   NA's                          :14596  
                                 a22c6                        a23       
 information technology/info systems:    1   not answered (9)   :    0  
 technology                         :    1   item not applicable:    0  
 not answered (999)                 :    0   yes                : 2430  
 item not applicable                :    0   no                 :11675  
 biology                            :    0   NA's               :  557  
 (Other)                            :    0                              
 NA's                               :14660                              
    a231a                           a231b      
 Length:14662       not answered (9)   :    0  
 Class :character   item not applicable:    0  
 Mode  :character   full award         :  182  
                    certain units only :   38  
                    NA's               :14442  
                                               
                                               
                         a231c1                              a231c2     
 health & social care       :   58   information technology (it):    2  
 business                   :   48   leisure and tourism        :    2  
 not stated                 :   27   science                    :    2  
 engineering                :   20   business                   :    1  
 information technology (it):   19   health & social care       :    1  
 (Other)                    :   61   (Other)                    :    2  
 NA's                       :14429   NA's                       :14652  
                 a231c3                      a231c4     
 leisure and tourism:    2   not answered (999) :    0  
 other gnvq         :    2   item not applicable:    0  
 not answered (999) :    0   performing arts    :    0  
 item not applicable:    0   art and design     :    0  
 performing arts    :    0   business           :    0  
 (Other)            :    0   (Other)            :    0  
 NA's               :14658   NA's               :14662  
                 a231c5                      a231c6         a232a          
 not answered (999) :    0   not answered (999) :    0   Length:14662      
 item not applicable:    0   item not applicable:    0   Class :character  
 performing arts    :    0   performing arts    :    0   Mode  :character  
 art and design     :    0   art and design     :    0                     
 business           :    0   business           :    0                     
 (Other)            :    0   (Other)            :    0                     
 NA's               :14662   NA's               :14662                     
                 a232b                        a232c1     
 not answered (9)   :    0   business            :  298  
 item not applicable:    0   health & social care:  254  
 full award         : 1073   leisure and tourism :  209  
 certain units only :  119   not stated          :  112  
 NA's               :13470   art and design      :  108  
                             (Other)             :  242  
                             NA's                :13439  
                              a232c2                      a232c3     
 information technology (it)     :    3   other gnvq         :    1  
 leisure and tourism             :    2   not answered (999) :    0  
 other gnvq                      :    2   item not applicable:    0  
 science                         :    1   performing arts    :    0  
 retail and distributive services:    1   art and design     :    0  
 (Other)                         :    0   (Other)            :    0  
 NA's                            :14653   NA's               :14661  
                 a232c4                      a232c5     
 not answered (999) :    0   not answered (999) :    0  
 item not applicable:    0   item not applicable:    0  
 performing arts    :    0   performing arts    :    0  
 art and design     :    0   art and design     :    0  
 business           :    0   business           :    0  
 (Other)            :    0   (Other)            :    0  
 NA's               :14662   NA's               :14662  
                 a232c6         a233a                           a233b      
 not answered (999) :    0   Length:14662       not answered (9)   :    0  
 item not applicable:    0   Class :character   item not applicable:    0  
 performing arts    :    0   Mode  :character   full award         :  940  
 art and design     :    0                      certain units only :   26  
 business           :    0                      NA's               :13696  
 (Other)            :    0                                                 
 NA's               :14662                                                 
                         a233c1                                   a233c2     
 business                   :  301   leisure and tourism             :    2  
 leisure and tourism        :  166   retail and distributive services:    1  
 health & social care       :  163   not answered (999)              :    0  
 art and design             :   88   item not applicable             :    0  
 information technology (it):   64   performing arts                 :    0  
 (Other)                    :  197   (Other)                         :    0  
 NA's                       :13683   NA's                            :14659  
                         a233c3                      a233c4     
 information technology (it):    1   other gnvq         :    1  
 not answered (999)         :    0   not answered (999) :    0  
 item not applicable        :    0   item not applicable:    0  
 performing arts            :    0   performing arts    :    0  
 art and design             :    0   art and design     :    0  
 (Other)                    :    0   (Other)            :    0  
 NA's                       :14661   NA's               :14661  
                 a233c5                      a233c6     
 other gnvq         :    1   other gnvq         :    1  
 not answered (999) :    0   not answered (999) :    0  
 item not applicable:    0   item not applicable:    0  
 performing arts    :    0   performing arts    :    0  
 art and design     :    0   art and design     :    0  
 (Other)            :    0   (Other)            :    0  
 NA's               :14661   NA's               :14661  
                 a24_1          a24nva1      
 not answered (9)   :    0   Min.   :0.0000  
 item not applicable:    0   1st Qu.:0.0000  
 yes                : 3243   Median :0.0000  
 no                 :10696   Mean   :0.1506  
 NA's               :  723   3rd Qu.:0.0000  
                             Max.   :3.0000  
                                             
                                                          a24n11     
 other - includes child development, hairdressing and beauty :  292  
 business & management (general)                             :  272  
 hotel & commercial catering                                 :  124  
 marketing sales & distribution                              :  123  
 vehicle maintenance & repair                                :  122  
 (Other)                                                     :  856  
 NA's                                                        :12873  
                             a24n12     
 languages & language studies   :    2  
 business & management (general):    1  
 office and secretarial skills  :    1  
 design (non-industrial)        :    1  
 religious studies              :    1  
 (Other)                        :    4  
 NA's                           :14652  
                                    a24n13     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n14     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n15     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n16     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n17     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n18         a24nvl1         a24nvl11    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.000  
 enterprises                           :    0   Median :1.000   Median :0.000  
 management skills systems & techniques:    0   Mean   :1.234   Mean   :0.211  
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.000  
 (Other)                               :    0   Max.   :3.000   Max.   :1.000  
 NA's                                  :14662   NA's   :12873   NA's   :12873  
    a24nvl12        a24nvl13        a24nvl18        a24nvl19    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :1.000   Median :0.000   Median :0.000   Median :0.000  
 Mean   :0.654   Mean   :0.228   Mean   :0.108   Mean   :0.033  
 3rd Qu.:1.000   3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:0.000  
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :12873   NA's   :12873   NA's   :12873   NA's   :12873  
    a24nva2        
 Min.   :0.000000  
 1st Qu.:0.000000  
 Median :0.000000  
 Mean   :0.009276  
 3rd Qu.:0.000000  
 Max.   :3.000000  
                   
                                                          a24n21     
 business & management (general)                             :   17  
 other - includes child development, hairdressing and beauty :   15  
 office and secretarial skills                               :   12  
 marketing sales & distribution                              :    8  
 hotel & commercial catering                                 :    8  
 (Other)                                                     :   53  
 NA's                                                        :14549  
                                    a24n22     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n23     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n24     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n25     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n26     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n27     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n28         a24nvl2         a24nvl21    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.00   
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.00   
 enterprises                           :    0   Median :1.000   Median :0.00   
 management skills systems & techniques:    0   Mean   :1.088   Mean   :0.15   
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.00   
 (Other)                               :    0   Max.   :3.000   Max.   :1.00   
 NA's                                  :14662   NA's   :14549   NA's   :14549  
    a24nvl22        a24nvl23        a24nvl28        a24nvl29    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :1.000   Median :0.000   Median :0.000   Median :0.000  
 Mean   :0.513   Mean   :0.363   Mean   :0.053   Mean   :0.009  
 3rd Qu.:1.000   3rd Qu.:1.000   3rd Qu.:0.000   3rd Qu.:0.000  
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :14549   NA's   :14549   NA's   :14549   NA's   :14549  
    a24nva3                                                    a24n31     
 Min.   :0.000000   information technology & computer applications:    5  
 1st Qu.:0.000000   office and secretarial skills                 :    2  
 Median :0.000000   financial management & accounting             :    1  
 Mean   :0.001432   public administration                         :    1  
 3rd Qu.:0.000000   languages & language studies                  :    1  
 Max.   :3.000000   (Other)                                       :    6  
                    NA's                                          :14646  
                                    a24n32     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n33     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n34     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n35     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n36     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n37     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24n38         a24nvl3         a24nvl31    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.00   
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.00   
 enterprises                           :    0   Median :1.000   Median :0.00   
 management skills systems & techniques:    0   Mean   :1.125   Mean   :0.25   
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.25   
 (Other)                               :    0   Max.   :3.000   Max.   :1.00   
 NA's                                  :14662   NA's   :14646   NA's   :14646  
    a24nvl32        a24nvl33        a24nvl38        a24nvl39    
 Min.   :0.000   Min.   :0.00    Min.   :0.000   Min.   :0.000  
 1st Qu.:0.000   1st Qu.:0.00    1st Qu.:0.000   1st Qu.:0.000  
 Median :0.000   Median :0.00    Median :0.000   Median :0.000  
 Mean   :0.312   Mean   :0.25    Mean   :0.188   Mean   :0.125  
 3rd Qu.:1.000   3rd Qu.:0.25    3rd Qu.:0.000   3rd Qu.:0.000  
 Max.   :1.000   Max.   :1.00    Max.   :1.000   Max.   :1.000  
 NA's   :14646   NA's   :14646   NA's   :14646   NA's   :14646  
   a24bta1         
 Length:14662      
 Class :character  
 Mode  :character  
                   
                   
                   
                   
                                                          a24b11     
 engineering/ technology/ manufacture (general)              :   20  
 mechanical engineering                                      :    6  
 vehicle maintenance & repair                                :    6  
 other - includes child development, hairdressing and beauty :    6  
 public administration                                       :    5  
 (Other)                                                     :   31  
 NA's                                                        :14588  
                                    a24b12     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b13     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b14     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b15     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b16     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b17     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b18         a24btc1         a24btc11    
 item not applicable                   :    0   Min.   :1       Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1       1st Qu.:0.000  
 enterprises                           :    0   Median :1       Median :0.000  
 management skills systems & techniques:    0   Mean   :1       Mean   :0.101  
 human resources management            :    0   3rd Qu.:1       3rd Qu.:0.000  
 (Other)                               :    0   Max.   :1       Max.   :1.000  
 NA's                                  :14662   NA's   :14593   NA's   :14593  
    a24btc12        a24btc13        a24btc18        a24btc19    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:1.000   1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.000   Median :0      
 Mean   :0.116   Mean   :0.029   Mean   :0.754   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14593   NA's   :14593   NA's   :14593   NA's   :14593  
   a24bta2                                                     a24b21     
 Length:14662       veterinary services & pet care                :   18  
 Class :character   public administration                         :   13  
 Mode  :character   theatre & dramatic arts                       :   10  
                    agricultural & horticultural studies (general):    7  
                    information technology & computer applications:    7  
                    (Other)                                       :   58  
                    NA's                                          :14549  
                                    a24b22     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b23     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b24     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b25     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b26     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b27     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b28         a24btc2         a24btc21    
 item not applicable                   :    0   Min.   :1.00    Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.00    1st Qu.:0.000  
 enterprises                           :    0   Median :1.00    Median :0.000  
 management skills systems & techniques:    0   Mean   :1.01    Mean   :0.072  
 human resources management            :    0   3rd Qu.:1.00    3rd Qu.:0.000  
 (Other)                               :    0   Max.   :2.00    Max.   :1.000  
 NA's                                  :14662   NA's   :14565   NA's   :14565  
    a24btc22        a24btc23        a24btc28        a24btc29    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:1.000   1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.000   Median :0      
 Mean   :0.072   Mean   :0.041   Mean   :0.825   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14565   NA's   :14565   NA's   :14565   NA's   :14565  
   a24bta3         
 Length:14662      
 Class :character  
 Mode  :character  
                   
                   
                   
                   
                                                          a24b31     
 other - includes child development, hairdressing and beauty :   73  
 theatre & dramatic arts                                     :   54  
 sports studies & combined sports                            :   47  
 design (non-industrial)                                     :   34  
 information technology & computer applications              :   34  
 (Other)                                                     :  343  
 NA's                                                        :14077  
                          a24b32     
 languages & language studies:    1  
 theatre & dramatic arts     :    1  
 mathematics                 :    1  
 electronic engineering      :    1  
 item not applicable         :    0  
 (Other)                     :    0  
 NA's                        :14658  
                                            a24b33     
 information technology & computer applications:    1  
 item not applicable                           :    0  
 business & management (general)               :    0  
 enterprises                                   :    0  
 management skills systems & techniques        :    0  
 (Other)                                       :    0  
 NA's                                          :14661  
                                    a24b34     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b35     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b36     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b37     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b38         a24btc3         a24btc31    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.000  
 enterprises                           :    0   Median :1.000   Median :0.000  
 management skills systems & techniques:    0   Mean   :1.009   Mean   :0.013  
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.000  
 (Other)                               :    0   Max.   :3.000   Max.   :1.000  
 NA's                                  :14662   NA's   :14123   NA's   :14123  
    a24btc32        a24btc33        a24btc38        a24btc39    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:1.000   1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.000   Median :0      
 Mean   :0.048   Mean   :0.096   Mean   :0.852   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14123   NA's   :14123   NA's   :14123   NA's   :14123  
   a24bta4         
 Length:14662      
 Class :character  
 Mode  :character  
                   
                   
                   
                   
                                                          a24b41     
 other - includes child development, hairdressing and beauty :    4  
 design (non-industrial)                                     :    3  
 mathematics                                                 :    3  
 mechanical engineering                                      :    3  
 not stated                                                  :    3  
 (Other)                                                     :   22  
 NA's                                                        :14624  
                                    a24b42     
 earth sciences                        :    1  
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 (Other)                               :    0  
 NA's                                  :14661  
                                    a24b43     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b44     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b45     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b46     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b47     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24b48         a24btc4         a24btc41    
 item not applicable                   :    0   Min.   :1.000   Min.   :0      
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0      
 enterprises                           :    0   Median :1.000   Median :0      
 management skills systems & techniques:    0   Mean   :1.034   Mean   :0      
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0      
 (Other)                               :    0   Max.   :2.000   Max.   :0      
 NA's                                  :14662   NA's   :14633   NA's   :14633  
    a24btc42        a24btc43        a24btc48        a24btc49    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:1.000   1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.000   Median :0      
 Mean   :0.069   Mean   :0.069   Mean   :0.897   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14633   NA's   :14633   NA's   :14633   NA's   :14633  
   a24cga1         
 Length:14662      
 Class :character  
 Mode  :character  
                   
                   
                   
                   
                                                          a24c11     
 electrical engineering                                      :   22  
 vehicle maintenance & repair                                :   18  
 electronic engineering                                      :   16  
 engineering/ technology/ manufacture (general)              :   13  
 other - includes child development, hairdressing and beauty :   10  
 (Other)                                                     :   68  
 NA's                                                        :14515  
                                    a24c12     
 languages & language studies          :    1  
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 (Other)                               :    0  
 NA's                                  :14661  
                                    a24c13     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c14     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c15     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c16     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c17     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c18         a24cgc1         a24cgc11    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.000  
 enterprises                           :    0   Median :1.000   Median :0.000  
 management skills systems & techniques:    0   Mean   :1.101   Mean   :0.295  
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:1.000  
 (Other)                               :    0   Max.   :3.000   Max.   :1.000  
 NA's                                  :14662   NA's   :14533   NA's   :14533  
    a24cgc12        a24cgc13        a24cgc18        a24cgc19    
 Min.   :0.000   Min.   :0.00    Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.00    1st Qu.:0.000   1st Qu.:0      
 Median :0.000   Median :0.00    Median :1.000   Median :0      
 Mean   :0.147   Mean   :0.07    Mean   :0.589   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.00    3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.00    Max.   :1.000   Max.   :0      
 NA's   :14533   NA's   :14533   NA's   :14533   NA's   :14533  
   a24cga2                                                     a24c21     
 Length:14662       electrical engineering                        :   10  
 Class :character   engineering/ technology/ manufacture (general):   10  
 Mode  :character   mathematics                                   :    5  
                    vehicle maintenance & repair                  :    5  
                    not stated                                    :    5  
                    (Other)                                       :   33  
                    NA's                                          :14594  
                                    a24c22     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c23     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c24     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c25     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c26     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c27     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c28         a24cgc2         a24cgc21    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.000  
 enterprises                           :    0   Median :1.000   Median :0.000  
 management skills systems & techniques:    0   Mean   :1.033   Mean   :0.033  
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.000  
 (Other)                               :    0   Max.   :2.000   Max.   :1.000  
 NA's                                  :14662   NA's   :14602   NA's   :14602  
    a24cgc22        a24cgc23        a24cgc28        a24cgc29    
 Min.   :0.000   Min.   :0.000   Min.   :0.00    Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.00    1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.00    Median :0      
 Mean   :0.267   Mean   :0.083   Mean   :0.65    Mean   :0      
 3rd Qu.:1.000   3rd Qu.:0.000   3rd Qu.:1.00    3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.00    Max.   :0      
 NA's   :14602   NA's   :14602   NA's   :14602   NA's   :14602  
   a24cga3                                             a24c31     
 Length:14662       vehicle maintenance & repair          :    3  
 Class :character   not stated                            :    3  
 Mode  :character   cooking & food & drinking preparation :    2  
                    mathematics                           :    2  
                    building/construction studies, general:    2  
                    (Other)                               :    8  
                    NA's                                  :14642  
                                    a24c32     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c33     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c34     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c35     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c36     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c37     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c38         a24cgc3         a24cgc31    
 item not applicable                   :    0   Min.   :1       Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1       1st Qu.:0.000  
 enterprises                           :    0   Median :1       Median :0.000  
 management skills systems & techniques:    0   Mean   :1       Mean   :0.056  
 human resources management            :    0   3rd Qu.:1       3rd Qu.:0.000  
 (Other)                               :    0   Max.   :1       Max.   :1.000  
 NA's                                  :14662   NA's   :14644   NA's   :14644  
    a24cgc32        a24cgc33        a24cgc38        a24cgc39    
 Min.   :0       Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0       1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0      
 Median :0       Median :0.000   Median :1.000   Median :0      
 Mean   :0       Mean   :0.389   Mean   :0.556   Mean   :0      
 3rd Qu.:0       3rd Qu.:1.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :0       Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14644   NA's   :14644   NA's   :14644   NA's   :14644  
   a24cga4         
 Length:14662      
 Class :character  
 Mode  :character  
                   
                   
                   
                   
                                                          a24c41     
 other - includes child development, hairdressing and beauty :   32  
 information technology & computer applications              :   21  
 mathematics                                                 :   14  
 vehicle maintenance & repair                                :   14  
 not stated                                                  :   13  
 (Other)                                                     :   87  
 NA's                                                        :14481  
                             a24c42     
 languages & language studies   :    2  
 mathematics                    :    1  
 item not applicable            :    0  
 business & management (general):    0  
 enterprises                    :    0  
 (Other)                        :    0  
 NA's                           :14659  
                                    a24c43     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c44     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c45     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c46     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c47     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24c48         a24cgc4         a24cgc41    
 item not applicable                   :    0   Min.   :1.00    Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.00    1st Qu.:0.000  
 enterprises                           :    0   Median :1.00    Median :0.000  
 management skills systems & techniques:    0   Mean   :1.14    Mean   :0.134  
 human resources management            :    0   3rd Qu.:1.00    3rd Qu.:0.000  
 (Other)                               :    0   Max.   :3.00    Max.   :1.000  
 NA's                                  :14662   NA's   :14498   NA's   :14498  
    a24cgc42        a24cgc43        a24cgc48        a24cgc49    
 Min.   :0.000   Min.   :0.00    Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.00    1st Qu.:0.000   1st Qu.:0      
 Median :0.000   Median :0.00    Median :1.000   Median :0      
 Mean   :0.183   Mean   :0.14    Mean   :0.683   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.00    3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.00    Max.   :1.000   Max.   :0      
 NA's   :14498   NA's   :14498   NA's   :14498   NA's   :14498  
   a24rsa1                                                     a24r11     
 Length:14662       information technology & computer applications:  142  
 Class :character   office and secretarial skills                 :   94  
 Mode  :character   not stated                                    :   15  
                    business & management (general)               :   14  
                    languages & language studies                  :    7  
                    (Other)                                       :   13  
                    NA's                                          :14377  
                                            a24r12     
 information technology & computer applications:    3  
 languages & language studies                  :    2  
 office and secretarial skills                 :    1  
 item not applicable                           :    0  
 business & management (general)               :    0  
 (Other)                                       :    0  
 NA's                                          :14656  
                                    a24r13     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r14     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r15     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r16     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r17     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r18         a24rsc1         a24rsc11    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.000  
 enterprises                           :    0   Median :1.000   Median :0.000  
 management skills systems & techniques:    0   Mean   :1.098   Mean   :0.242  
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.000  
 (Other)                               :    0   Max.   :3.000   Max.   :1.000  
 NA's                                  :14662   NA's   :14398   NA's   :14398  
    a24rsc12        a24rsc13        a24rsc18        a24rsc19    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.000   Median :0      
 Mean   :0.205   Mean   :0.068   Mean   :0.583   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14398   NA's   :14398   NA's   :14398   NA's   :14398  
   a24rsa2                                                     a24r21     
 Length:14662       office and secretarial skills                 :   10  
 Class :character   information technology & computer applications:    7  
 Mode  :character   business & management (general)               :    6  
                    not stated                                    :    3  
                    public administration                         :    1  
                    (Other)                                       :    3  
                    NA's                                          :14632  
                                    a24r22     
 office and secretarial skills         :    1  
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 (Other)                               :    0  
 NA's                                  :14661  
                                    a24r23     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r24     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r25     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r26     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r27     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r28         a24rsc2         a24rsc21    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.000  
 enterprises                           :    0   Median :1.000   Median :0.000  
 management skills systems & techniques:    0   Mean   :1.036   Mean   :0.071  
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.000  
 (Other)                               :    0   Max.   :2.000   Max.   :1.000  
 NA's                                  :14662   NA's   :14634   NA's   :14634  
    a24rsc22        a24rsc23        a24rsc28        a24rsc29    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.000   Median :0      
 Mean   :0.214   Mean   :0.071   Mean   :0.679   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14634   NA's   :14634   NA's   :14634   NA's   :14634  
   a24rsa3         
 Length:14662      
 Class :character  
 Mode  :character  
                   
                   
                   
                   
                                                          a24r31     
 office and secretarial skills                               :    5  
 business & management (general)                             :    2  
 information technology & computer applications              :    2  
 insufficient info                                           :    1  
 other - includes child development, hairdressing and beauty :    1  
 (Other)                                                     :    0  
 NA's                                                        :14651  
                                    a24r32     
 financial management & accounting     :    1  
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 (Other)                               :    0  
 NA's                                  :14661  
                                    a24r33     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r34     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r35     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r36     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r37     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r38         a24rsc3         a24rsc31    
 item not applicable                   :    0   Min.   :1       Min.   :0      
 business & management (general)       :    0   1st Qu.:1       1st Qu.:0      
 enterprises                           :    0   Median :1       Median :0      
 management skills systems & techniques:    0   Mean   :1       Mean   :0      
 human resources management            :    0   3rd Qu.:1       3rd Qu.:0      
 (Other)                               :    0   Max.   :1       Max.   :0      
 NA's                                  :14662   NA's   :14651   NA's   :14651  
    a24rsc32        a24rsc33        a24rsc38       a24rsa4         
 Min.   :0       Min.   :0.000   Min.   :0.000   Length:14662      
 1st Qu.:0       1st Qu.:0.000   1st Qu.:1.000   Class :character  
 Median :0       Median :0.000   Median :1.000   Mode  :character  
 Mean   :0       Mean   :0.182   Mean   :0.818                     
 3rd Qu.:0       3rd Qu.:0.000   3rd Qu.:1.000                     
 Max.   :0       Max.   :1.000   Max.   :1.000                     
 NA's   :14651   NA's   :14651   NA's   :14651                     
                                            a24r41     
 information technology & computer applications:   48  
 office and secretarial skills                 :   12  
 not stated                                    :    5  
 languages & language studies                  :    3  
 financial management & accounting             :    2  
 (Other)                                       :    4  
 NA's                                          :14588  
                               a24r42     
 financial management & accounting:    1  
 languages & language studies     :    1  
 item not applicable              :    0  
 business & management (general)  :    0  
 enterprises                      :    0  
 (Other)                          :    0  
 NA's                             :14660  
                                    a24r43     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r44     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r45     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r46     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r47     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24r48         a24rsc4         a24rsc41    
 item not applicable                   :    0   Min.   :1.000   Min.   :0.000  
 business & management (general)       :    0   1st Qu.:1.000   1st Qu.:0.000  
 enterprises                           :    0   Median :1.000   Median :0.000  
 management skills systems & techniques:    0   Mean   :1.091   Mean   :0.182  
 human resources management            :    0   3rd Qu.:1.000   3rd Qu.:0.000  
 (Other)                               :    0   Max.   :2.000   Max.   :1.000  
 NA's                                  :14662   NA's   :14596   NA's   :14596  
    a24rsc42        a24rsc43        a24rsc48        a24rsc49    
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0      
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0      
 Median :0.000   Median :0.000   Median :1.000   Median :0      
 Mean   :0.136   Mean   :0.045   Mean   :0.727   Mean   :0      
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0      
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :0      
 NA's   :14596   NA's   :14596   NA's   :14596   NA's   :14596  
                                                          a24oq1     
 other qualification: band not known, i.e. all other courses :   84  
 other band c n.e.c. at nvq level not stated                 :   37  
 professional qualifications (further education codes 501-999:   22  
 qualification not stated                                    :   17  
 unclear/uncodeable                                          :   14  
 (Other)                                                     :   26  
 NA's                                                        :14462  
                                                          a24o11     
 information technology & computer applications              :   29  
 other - includes child development, hairdressing and beauty :   29  
 nursing                                                     :   17  
 sports studies & combined sports                            :   12  
 languages & language studies                                :   11  
 (Other)                                                     :  102  
 NA's                                                        :14462  
                             a24o12     
 history                        :    1  
 science & technology (general) :    1  
 item not applicable            :    0  
 business & management (general):    0  
 enterprises                    :    0  
 (Other)                        :    0  
 NA's                           :14660  
                                                          a24o13     
 mathematics                                                 :    1  
 other - includes child development, hairdressing and beauty :    1  
 item not applicable                                         :    0  
 business & management (general)                             :    0  
 enterprises                                                 :    0  
 (Other)                                                     :    0  
 NA's                                                        :14660  
                                    a24o14     
 electrical engineering                :    1  
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 (Other)                               :    0  
 NA's                                  :14661  
                                    a24o15     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o16     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o17     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o18                      a24ol1     
 item not applicable                   :    0   item not applicable:    0  
 business & management (general)       :    0   level 1            :   10  
 enterprises                           :    0   level 2            :    9  
 management skills systems & techniques:    0   level 3            :    7  
 human resources management            :    0   not sure           :  137  
 (Other)                               :    0   not answered       :   37  
 NA's                                  :14662   NA's               :14462  
                                                          a24oq2     
 other qualification: band not known, i.e. all other courses :    7  
 unclear/uncodeable                                          :    2  
 nvq (not rsa, btec or c & g) level 4                        :    1  
 professional qualifications (further education codes 501-999:    1  
 no qualification                                            :    1  
 (Other)                                                     :    0  
 NA's                                                        :14650  
                             a24o21     
 dance                          :    2  
 business & management (general):    1  
 office and secretarial skills  :    1  
 fabric crafts                  :    1  
 history                        :    1  
 (Other)                        :    6  
 NA's                           :14650  
                                    a24o22     
 languages & language studies          :    1  
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 (Other)                               :    0  
 NA's                                  :14661  
                                    a24o23     
 languages & language studies          :    1  
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 (Other)                               :    0  
 NA's                                  :14661  
                                    a24o24     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o25     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o26     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o27     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o28                      a24ol2     
 item not applicable                   :    0   item not applicable:    0  
 business & management (general)       :    0   level 1            :    0  
 enterprises                           :    0   level 2            :    1  
 management skills systems & techniques:    0   level 3            :    0  
 human resources management            :    0   not sure           :    8  
 (Other)                               :    0   not answered       :    3  
 NA's                                  :14662   NA's               :14650  
                                                          a24oq3     
 other qualification: band not known, i.e. all other courses :    3  
 no qualification                                            :    1  
 qualification not stated                                    :    1  
 item not applicable                                         :    0  
 part 1 gnvq foundation                                      :    0  
 (Other)                                                     :    0  
 NA's                                                        :14657  
                             a24o31     
 business & management (general):    1  
 office and secretarial skills  :    1  
 dance                          :    1  
 theatre & dramatic arts        :    1  
 music performance              :    1  
 (Other)                        :    0  
 NA's                           :14657  
                                    a24o32     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o33     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o34     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o35     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o36     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o37     
 item not applicable                   :    0  
 business & management (general)       :    0  
 enterprises                           :    0  
 management skills systems & techniques:    0  
 human resources management            :    0  
 (Other)                               :    0  
 NA's                                  :14662  
                                    a24o38                      a24ol3     
 item not applicable                   :    0   item not applicable:    0  
 business & management (general)       :    0   level 1            :    0  
 enterprises                           :    0   level 2            :    0  
 management skills systems & techniques:    0   level 3            :    0  
 human resources management            :    0   not sure           :    3  
 (Other)                               :    0   not answered       :    2  
 NA's                                  :14662   NA's               :14657  
                  a25                         a26            a27      
 not answered (9)   :    0   not answered (9)   :   0   sep    :1127  
 item not applicable:    0   item not applicable:   0   jul    : 780  
 yes                :10232   yes                :7853   aug    : 737  
 no                 : 4272   no                 :2364   jun    : 729  
 NA's               :  158   NA's               :4445   oct    : 723  
                                                        (Other):3757  
                                                        NA's   :6809  
      a28                a30            a31                          a32      
 Min.   :102    1-9        :2119   Min.   : 0.000   not answered (9)   :   0  
 1st Qu.:621    10-24      :2024   1st Qu.: 0.000   item not applicable:   0  
 Median :720    100 or more:1442   Median : 4.000   employee           :7588  
 Mean   :704    25-49      :1289   Mean   : 4.304   self-employee      : 110  
 3rd Qu.:792    50-99      : 833   3rd Qu.: 7.000   NA's               :6964  
 Max.   :998    (Other)    :   0   Max.   :18.000                             
 NA's   :6818   NA's       :6955                                              
                  a33                        a34           a35_1       
 not answered (9)   :   0   not answered (9)   :   0   Min.   :  1.00  
 item not applicable:   0   item not applicable:   0   1st Qu.: 25.00  
 permanent          :5006   yes                :1133   Median : 40.00  
 temporary          :1816   no                 :6181   Mean   : 52.61  
 not sure           : 936   not sure           : 458   3rd Qu.: 65.00  
 NA's               :6904   NA's               :6890   Max.   :450.00  
                                                       NA's   :9489    
     a35_2            a35              a36       
 Min.   : 12.0   Min.   :  2.77   Min.   : 1.00  
 1st Qu.:100.0   1st Qu.: 23.08   1st Qu.: 8.00  
 Median :160.0   Median : 36.92   Median :14.00  
 Mean   :212.2   Mean   : 48.97   Mean   :20.04  
 3rd Qu.:280.0   3rd Qu.: 64.62   3rd Qu.:36.00  
 Max.   :900.0   Max.   :207.69   Max.   :80.00  
 NA's   :12454   NA's   :12454    NA's   :7112   
                                  a37           a37a_1           a37a_2      
 not answered (9)                   :   0   Min.   :  5.00   Min.   : 39.97  
 item not applicable                :   0   1st Qu.: 37.12   1st Qu.:140.00  
 one job or training place          :7149   Median : 51.50   Median :200.00  
 more than one job or training place: 526   Mean   : 67.88   Mean   :232.00  
 NA's                               :6987   3rd Qu.: 80.00   3rd Qu.:300.00  
                                            Max.   :300.00   Max.   :666.21  
                                            NA's   :14336    NA's   :14499   
      a37a             a37b                        a38      
 Min.   :  9.22   Min.   : 1.00   not answered (9)   :   0  
 1st Qu.: 32.31   1st Qu.:12.00   item not applicable:   0  
 Median : 46.15   Median :16.00   yes                :1929  
 Mean   : 53.54   Mean   :20.66   no                 :4899  
 3rd Qu.: 69.23   3rd Qu.:27.00   not sure           : 863  
 Max.   :153.74   Max.   :60.00   NA's               :6971  
 NA's   :14499    NA's   :14201                             
                              a38_2                        a39a     
 not answered (9)                :    0   not answered (9)   :   0  
 item not applicable             :    0   item not applicable:   0  
 yes                             : 1734   yes                :1166  
 no                              :  106   no                 :5828  
 i have not received any training:   21   not sure           : 660  
 my training has not yet started :   61   NA's               :7008  
 NA's                            :12740                             
                         a39b                        a40       
 modern apprenticeship (ma):  544   not answered (9)   :    0  
 youth training (yt)       :  420   item not applicable:    0  
 national trainee (ntr)    :   49   yes                :  955  
 unclear                   :   31   no                 :  156  
 other                     :   21   NA's               :13551  
 (Other)                   :   65                              
 NA's                      :13532                              
                      a41                         a42       
 not answered (9)       :    0   not answered (9)   :    0  
 item not applicable    :    0   item not applicable:    0  
 a full-time job        :  998   yes                :   18  
 a part-time job        :   58   no                 :   48  
 it is not part of a job:   68   NA's               :14596  
 NA's                   :13538                              
                                                            
                  a43                        a44_1     
 not answered (9)   :    0   not answered (9)   :   0  
 item not applicable:    0   item not applicable:   0  
 yes                :  746   yes                :3668  
 no                 :  291   no                 :4019  
 NA's               :13625   NA's               :6975  
                                                       
                                                       
                 a44_2                       a45_1     
 not answered (9)   :    0   not answered (9)   :   0  
 item not applicable:    0   item not applicable:   0  
 yes                : 2081   yes                :1174  
 no                 : 1564   no                 :6484  
 NA's               :11017   NA's               :7004  
                                                       
                                                       
                 a45_2                       a46             a47       
 not answered (9)   :   0   not answered (9)   :    0   Min.   :1.000  
 item not applicable:   0   item not applicable:    0   1st Qu.:1.000  
 yes                : 348   yes                :  661   Median :1.000  
 no                 :5847   no                 :  474   Mean   :1.049  
 NA's               :8467   NA's               :13527   3rd Qu.:1.000  
                                                        Max.   :3.000  
                                                        NA's   :13559  
      a471            a472            a473            a474      
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :0.000   Median :0.000   Median :0.000   Median :0.000  
 Mean   :0.334   Mean   :0.032   Mean   :0.129   Mean   :0.336  
 3rd Qu.:1.000   3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:1.000  
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :13559   NA's   :13559   NA's   :13559   NA's   :13559  
      a475                       a48_1           a48_2       
 Min.   :0.000   not answered (9)   :    0   Min.   : 1.000  
 1st Qu.:0.000   item not applicable:    0   1st Qu.: 4.000  
 Median :0.000   yes                :  503   Median : 4.000  
 Mean   :0.218   no                 :  636   Mean   : 3.678  
 3rd Qu.:0.000   NA's               :13523   3rd Qu.: 4.000  
 Max.   :1.000                               Max.   :10.000  
 NA's   :13559                               NA's   :14181   
                 a49_1           a49_2a          a49_2b     
 not answered (9)   :    0   Min.   :1.000   Min.   : 1.00  
 item not applicable:    0   1st Qu.:1.000   1st Qu.: 5.00  
 yes                :  182   Median :1.000   Median :12.00  
 no                 :  940   Mean   :2.371   Mean   :13.68  
 NA's               :13540   3rd Qu.:4.000   3rd Qu.:20.00  
                             Max.   :8.000   Max.   :52.00  
                             NA's   :14600   NA's   :14556  
                  a50                            a51       
 not answered (9)   :    0   not answered (9)      :    0  
 item not applicable:    0   item not applicable   :    0  
 excellent          :  329   too much              :   31  
 good               :  596   not enough            :  169  
 fair               :  172   about the right amount:  923  
 poor               :   29   NA's                  :13539  
 NA's               :13536                                 
                                        a52                        a52a     
 not answered (9)                         :   0   not answered (9)   :   0  
 item not applicable                      :   0   item not applicable:   0  
 yes full-time work (over 30 hours a week):2294   yes                : 340  
 yes part-time work                       :5439   no                 :5177  
 yes an occasional job                    : 776   NA's               :9145  
 no                                       :5947                             
 NA's                                     : 206                             
                  a52b                       a52c     
 not answered (9)   :   0   not answered (9)   :   0  
 item not applicable:   0   item not applicable:   0  
 yes                : 313   yes                : 391  
 no                 :5118   no                 :5081  
 NA's               :9231   NA's               :9190  
                                                      
                                                      
                 a53_1                      a53_2      
 not answered (9)   :   0   not answered (9)   :    0  
 item not applicable:   0   item not applicable:    0  
 yes                :2011   yes                : 1738  
 no                 :3799   no                 :  251  
 NA's               :8852   NA's               :12673  
                                                       
                                                       
                                                          a53_3      
 i am a full time student                                    : 3411  
 i am pregnant/looking after home/children/family            :   66  
 i believe there is nothing available                        :   61  
 other                                                       :   42  
 waiting to start a new job/government supported training/tra:   31  
 (Other)                                                     :  141  
 NA's                                                        :10910  
      a54a            a54b                       a55_1           a55_2a      
 Min.   :  1.0   Min.   :  1.0   not answered (9)   :    0   Min.   :  1.05  
 1st Qu.:100.0   1st Qu.: 80.0   item not applicable:    0   1st Qu.: 11.00  
 Median :140.0   Median :100.0   yes                :  670   Median : 12.76  
 Mean   :154.7   Mean   :118.3   no                 :13429   Mean   : 23.04  
 3rd Qu.:180.0   3rd Qu.:140.0   NA's               :  563   3rd Qu.: 30.00  
 Max.   :900.0   Max.   :900.0                               Max.   :100.17  
 NA's   :12011   NA's   :11863                               NA's   :14253   
     a55_2b           a55_2           a56_1              a56_2          
 Min.   :  1.00   Min.   :  0.50   Length:14662       Length:14662      
 1st Qu.: 30.00   1st Qu.: 11.00   Class :character   Class :character  
 Median : 59.20   Median : 15.00   Mode  :character   Mode  :character  
 Mean   : 60.86   Mean   : 24.83                                        
 3rd Qu.: 77.80   3rd Qu.: 34.70                                        
 Max.   :200.10   Max.   :100.17                                        
 NA's   :14531    NA's   :14122                                         
    a56_3a              a56_3b     
 Length:14662       Min.   : 1.00  
 Class :character   1st Qu.: 1.00  
 Mode  :character   Median : 1.00  
                    Mean   : 1.69  
                    3rd Qu.: 2.00  
                    Max.   :23.00  
                    NA's   :3231   
                                               a56_4a          a56_4b      
 other                                            :  452   Min.   : 1.000  
 grandparent(s)                                   :  381   1st Qu.: 1.000  
 spouse/partner (including boy/girlfriend, fianc0):  113   Median : 1.000  
 respondent's own child(ren)                      :   33   Mean   : 1.538  
 not answered (9)                                 :    0   3rd Qu.: 2.000  
 (Other)                                          :    0   Max.   :12.000  
 NA's                                             :13683   NA's   :13632   
    a56_5                           a57fa                       a57ma     
 Length:14662       not answered (9)   :    0   not answered (9)   :   0  
 Class :character   item not applicable:    0   item not applicable:   0  
 Mode  :character   yes                :11423   yes                :7734  
                    no                 : 2005   no                 :6189  
                    NA's               : 1234   NA's               : 739  
                                                                          
                                                                          
     a57fb         a57mb                       a57fe     
 Min.   :100   Min.   :101.0   not answered (9)   :   0  
 1st Qu.:242   1st Qu.:400.0   item not applicable:   0  
 Median :532   Median :644.0   yes                :3332  
 Mean   :571   Mean   :621.5   no                 :9584  
 3rd Qu.:889   3rd Qu.:958.0   NA's               :1746  
 Max.   :998   Max.   :998.0                             
 NA's   :7     NA's   :1                                 
                 a57me                       a57ff     
 not answered (9)   :    0   not answered (9)   :   0  
 item not applicable:    0   item not applicable:   0  
 yes                : 1297   yes                :3320  
 no                 :11577   no                 :6510  
 NA's               : 1788   not sure           :3220  
                             NA's               :1612  
                                                       
                 a57mf                      a57fg     
 not answered (9)   :   0   not answered (9)   :   0  
 item not applicable:   0   item not applicable:   0  
 yes                :3204   yes                :2629  
 no                 :7297   no                 :7787  
 not sure           :2838   not sure           :2629  
 NA's               :1323   NA's               :1617  
                                                      
                 a57mg                       a58       
 not answered (9)   :   0   white              :12993  
 item not applicable:   0   indian             :  436  
 yes                :1937   pakistani          :  280  
 no                 :8914   mixed ethnic origin:  126  
 not sure           :2458   bangladeshi        :  112  
 NA's               :1353   (Other)            :  544  
                            NA's               :  171  
                  a59       
 not answered (9)   :    0  
 item not applicable:    0  
 yes                :  577  
 no                 :13865  
 NA's               :  220  
                            
                            
                                                           a60       
 owned by your parents or yourself                           :11671  
 rented from the council                                     : 1736  
 rented privately                                            :  433  
 rented from a housing association                           :  339  
 house/accommodation comes with the job (including police/arm:   93  
 (Other)                                                     :  114  
 NA's                                                        :  276  
                             a61            a62             a621        
 never                         :9414   Min.   :1.000   Min.   :0.00000  
 for the odd day or lesson     :3710   1st Qu.:1.000   1st Qu.:0.00000  
 for particular days or lessons: 795   Median :1.000   Median :0.00000  
 for several days at a time    : 284   Mean   :1.002   Mean   :0.00648  
 for weeks at a time           : 246   3rd Qu.:1.000   3rd Qu.:0.00000  
 (Other)                       :   0   Max.   :2.000   Max.   :1.00000  
 NA's                          : 213   NA's   :146     NA's   :146      
      a622            a623                        a63a     
 Min.   :0.000   Min.   :0.000   not answered (9)   :   0  
 1st Qu.:0.000   1st Qu.:1.000   item not applicable:   0  
 Median :0.000   Median :1.000   agree              :3815  
 Mean   :0.058   Mean   :0.938   disagree           :4583  
 3rd Qu.:0.000   3rd Qu.:1.000   don't know         :6100  
 Max.   :1.000   Max.   :1.000   NA's               : 164  
 NA's   :146     NA's   :146                               
                  a63b                       a63c      
 not answered (9)   :   0   not answered (9)   :    0  
 item not applicable:   0   item not applicable:    0  
 agree              :5762   agree              : 1004  
 disagree           :5733   disagree           :12734  
 don't know         :2967   don't know         :  749  
 NA's               : 200   NA's               :  175  
                                                       
                  a63d                        a63e          change 
 not answered (9)   :    0   not answered (9)   :   0   Min.   :0  
 item not applicable:    0   item not applicable:   0   1st Qu.:0  
 agree              :10738   agree              :9402   Median :0  
 disagree           : 1885   disagree           :3369   Mean   :0  
 don't know         : 1857   don't know         :1707   3rd Qu.:0  
 NA's               :  182   NA's               : 184   Max.   :0  
                                                                   
    change1          change2          change3          change4      
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:1.0000  
 Median :1.0000   Median :0.0000   Median :1.0000   Median :1.0000  
 Mean   :0.6865   Mean   :0.3265   Mean   :0.6735   Mean   :0.8269  
 3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:1.0000  
 Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
                                                                    
     s1wexp     s1wexp1          s1wexp2          s1wexp3      
 Min.   :0   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0   1st Qu.:1.0000   1st Qu.:1.0000   1st Qu.:0.0000  
 Median :0   Median :1.0000   Median :1.0000   Median :0.0000  
 Mean   :0   Mean   :0.9437   Mean   :0.9134   Mean   :0.1851  
 3rd Qu.:0   3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:0.0000  
 Max.   :0   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
                                                               
    s1wexp4          s1wexp5          s1wexp6           s1wexp7        
 Min.   :0.0000   Min.   :0.0000   Min.   :0.00000   Min.   :0.000000  
 1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:0.000000  
 Median :0.0000   Median :0.0000   Median :0.00000   Median :0.000000  
 Mean   :0.4935   Mean   :0.2058   Mean   :0.02762   Mean   :0.001364  
 3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:0.00000   3rd Qu.:0.000000  
 Max.   :1.0000   Max.   :1.0000   Max.   :1.00000   Max.   :1.000000  
                                                                       
    s1wexp8           s1wexp9            s1nra       s1nra1      
 Min.   :0.00000   Min.   :0.00000   Min.   :0   Min.   :0.0000  
 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0   1st Qu.:1.0000  
 Median :0.00000   Median :0.00000   Median :0   Median :1.0000  
 Mean   :0.05627   Mean   :0.08655   Mean   :0   Mean   :0.8776  
 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0   3rd Qu.:1.0000  
 Max.   :1.00000   Max.   :1.00000   Max.   :0   Max.   :1.0000  
                                                                 
     s1nra2          s1nra3           s1nra4           s1nra5       
 Min.   :0.000   Min.   :0.0000   Min.   :0.0000   Min.   :0.00000  
 1st Qu.:0.000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.00000  
 Median :1.000   Median :0.0000   Median :0.0000   Median :0.00000  
 Mean   :0.627   Mean   :0.4314   Mean   :0.1711   Mean   :0.09637  
 3rd Qu.:1.000   3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:0.00000  
 Max.   :1.000   Max.   :1.0000   Max.   :1.0000   Max.   :1.00000  
                                                                    
     s1nra6            s1nra7            s1csown       s1csown1    
 Min.   :0.00000   Min.   :0.000000   Min.   :0     Min.   :0.000  
 1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0     1st Qu.:1.000  
 Median :0.00000   Median :0.000000   Median :0     Median :1.000  
 Mean   :0.01971   Mean   :0.006275   Mean   :0     Mean   :0.953  
 3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0     3rd Qu.:1.000  
 Max.   :1.00000   Max.   :1.000000   Max.   :0     Max.   :1.000  
                                      NA's   :701   NA's   :701    
    s1csown2         s1csown3         s1csown4         s1csown5    
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.000  
 1st Qu.:1.0000   1st Qu.:1.0000   1st Qu.:0.0000   1st Qu.:0.000  
 Median :1.0000   Median :1.0000   Median :0.0000   Median :0.000  
 Mean   :0.7984   Mean   :0.7973   Mean   :0.4499   Mean   :0.047  
 3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:0.000  
 Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.000  
 NA's   :701      NA's   :701      NA's   :701      NA's   :701    
     s1csgp       s1csgp1          s1csgp2          s1csgp3      
 Min.   :0     Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0     1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
 Median :0     Median :1.0000   Median :1.0000   Median :1.0000  
 Mean   :0     Mean   :0.6324   Mean   :0.5189   Mean   :0.5123  
 3rd Qu.:0     3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:1.0000  
 Max.   :0     Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
 NA's   :701   NA's   :701      NA's   :701      NA's   :701     
    s1csgp4          s1csgp5           s1car       s1car1      
 Min.   :0.0000   Min.   :0.0000   Min.   :0   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0   1st Qu.:1.0000  
 Median :0.0000   Median :0.0000   Median :0   Median :1.0000  
 Mean   :0.2583   Mean   :0.3676   Mean   :0   Mean   :0.8558  
 3rd Qu.:1.0000   3rd Qu.:1.0000   3rd Qu.:0   3rd Qu.:1.0000  
 Max.   :1.0000   Max.   :1.0000   Max.   :0   Max.   :1.0000  
 NA's   :701      NA's   :701                                  
     s1car2            s1car3           s1car4          s1car5       
 Min.   :0.00000   Min.   :0.0000   Min.   :0.000   Min.   :0.00000  
 1st Qu.:0.00000   1st Qu.:0.0000   1st Qu.:0.000   1st Qu.:0.00000  
 Median :0.00000   Median :0.0000   Median :0.000   Median :0.00000  
 Mean   :0.06056   Mean   :0.4709   Mean   :0.263   Mean   :0.05995  
 3rd Qu.:0.00000   3rd Qu.:1.0000   3rd Qu.:1.000   3rd Qu.:0.00000  
 Max.   :1.00000   Max.   :1.0000   Max.   :1.000   Max.   :1.00000  
                                                                     
     s1car6             s1car7           s1car9       
 Min.   :0.000000   Min.   :0.0000   Min.   :0.00000  
 1st Qu.:0.000000   1st Qu.:0.0000   1st Qu.:0.00000  
 Median :0.000000   Median :0.0000   Median :0.00000  
 Mean   :0.001432   Mean   :0.1343   Mean   :0.00989  
 3rd Qu.:0.000000   3rd Qu.:0.0000   3rd Qu.:0.00000  
 Max.   :1.000000   Max.   :1.0000   Max.   :1.00000  
                                                      
                     s1sch                         s1acqu         s1qstd 
 state school (other)   :11114   5+ gcses!at a*-c     :8415   Min.   :0  
 state school (gm)      : 2495   1-4 gcses!at a*-c    :3709   1st Qu.:0  
 independent school     : 1053   5+ gcses!at d-g      :1451   Median :0  
 not answered (9)       :    0   none!reported        : 757   Mean   :0  
 schedule not obtained  :    0   1-4 gcses!at d-g     : 330   3rd Qu.:0  
 schedule not applicable:    0   schedule not obtained:   0   Max.   :0  
 (Other)                :    0   (Other)              :   0              
    s1qstd01         s1qstd02         s1qstd03         s1qstd04     
 Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
 Median :0.0000   Median :0.0000   Median :0.0000   Median :0.0000  
 Mean   :0.4772   Mean   :0.1382   Mean   :0.1529   Mean   :0.1087  
 3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:0.0000   3rd Qu.:0.0000  
 Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
                                                                    
    s1qstd05          s1qstd06          s1qstd07         s1qstd08       
 Min.   :0.00000   Min.   :0.00000   Min.   :0.0000   Min.   :0.000000  
 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.0000   1st Qu.:0.000000  
 Median :0.00000   Median :0.00000   Median :0.0000   Median :0.000000  
 Mean   :0.01241   Mean   :0.01446   Mean   :0.1075   Mean   :0.008116  
 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.0000   3rd Qu.:0.000000  
 Max.   :1.00000   Max.   :1.00000   Max.   :1.0000   Max.   :1.000000  
                                                                        
    s1qstd09           s1qstd10     
 Min.   :0.000000   Min.   :0.0000  
 1st Qu.:0.000000   1st Qu.:0.0000  
 Median :0.000000   Median :0.0000  
 Mean   :0.001364   Mean   :0.1768  
 3rd Qu.:0.000000   3rd Qu.:0.0000  
 Max.   :1.000000   Max.   :1.0000  
                                    
                                         s1loced    
 state school                                :4884  
 cfe (state system)                          :3198  
 sixth form college (state system)           :1617  
 independent/private school                  : 860  
 institution not stated (difft. from year 11): 245  
 (Other)                                     : 202  
 NA's                                        :3656  
                       s1act1          s1wtrn        s1wtrn1     
 ft education:            :10901   Min.   :0      Min.   :0.000  
 gst:                     : 1398   1st Qu.:0      1st Qu.:0.000  
 ft job:                  : 1182   Median :0      Median :0.000  
 out of work / unemployed::  604   Mean   :0      Mean   :0.175  
 pt job:                  :  332   3rd Qu.:0      3rd Qu.:0.000  
 doing something else:    :  154   Max.   :0      Max.   :1.000  
 (Other)                  :   91   NA's   :6693   NA's   :6693   
    s1wtrn2         s1wtrn3         s1wtrn4         s1wtrn5     
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :0.000   Median :0.000   Median :0.000   Median :0.000  
 Mean   :0.142   Mean   :0.261   Mean   :0.083   Mean   :0.063  
 3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0.000   3rd Qu.:0.000  
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :6693    NA's   :6693    NA's   :6693    NA's   :6693   
    s1wtrn6         s1wtrn7                                  s1gst      
 Min.   :0.000   Min.   :0.000   modern apprenticeship (ma)     :  535  
 1st Qu.:0.000   1st Qu.:0.000   youth training (yt)            :  410  
 Median :0.000   Median :1.000   didn't answer question on type :  333  
 Mean   :0.023   Mean   :0.627   other training (write in below):   72  
 3rd Qu.:0.000   3rd Qu.:1.000   national traineeship (ntr)     :   48  
 Max.   :1.000   Max.   :1.000   (Other)                        :    0  
 NA's   :6693    NA's   :6693    NA's                           :13264  
      pseg       pseg1            pseg2            pseg3            pseg4      
 Min.   :0   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000   Min.   :0.000  
 1st Qu.:0   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.000  
 Median :0   Median :0.0000   Median :0.0000   Median :0.0000   Median :0.000  
 Mean   :0   Mean   :0.2299   Mean   :0.2064   Mean   :0.3141   Mean   :0.108  
 3rd Qu.:0   3rd Qu.:0.0000   3rd Qu.:0.0000   3rd Qu.:1.0000   3rd Qu.:0.000  
 Max.   :0   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000   Max.   :1.000  
                                                                               
     pseg5             pseg6              pseg7            pseg8       
 Min.   :0.00000   Min.   :0.000000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.0000   1st Qu.:0.0000  
 Median :0.00000   Median :0.000000   Median :0.0000   Median :0.0000  
 Mean   :0.03581   Mean   :0.003819   Mean   :0.1019   Mean   :0.4363  
 3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.0000   3rd Qu.:1.0000  
 Max.   :1.00000   Max.   :1.000000   Max.   :1.0000   Max.   :1.0000  
                                                                       
     pseg9                     s1acqe                             s1emplo    
 Min.   :0.000   5+ gcses at a*-c :8465   in job, but unknown if ft/pt:5169  
 1st Qu.:0.000   1-4 gcses at a*-c:3676   gst                         :1398  
 Median :0.000   5+ gcses at d-g  :1448   ft job                      :1182  
 Mean   :0.458   none reported    : 745   pt job                      : 332  
 3rd Qu.:1.000   1-4 gcses at d-g : 328   not answered (9)            :   0  
 Max.   :1.000   not answered (9) :   0   (Other)                     :   0  
                 (Other)          :   0   NA's                        :6581  
    s1ed_tr     s1ed_tr1         s1ed_tr2          s1ed_tr3       
 Min.   :0   Min.   :0.0000   Min.   :0.00000   Min.   :0.000000  
 1st Qu.:0   1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:0.000000  
 Median :0   Median :1.0000   Median :0.00000   Median :0.000000  
 Mean   :0   Mean   :0.7435   Mean   :0.09535   Mean   :0.001569  
 3rd Qu.:0   3rd Qu.:1.0000   3rd Qu.:0.00000   3rd Qu.:0.000000  
 Max.   :0   Max.   :1.0000   Max.   :1.00000   Max.   :1.000000  
                                                                  
    s1ed_tr4          s1ed_tr5          s1ed_tr6         s1ed_tr7     
 Min.   :0.00000   Min.   :0.00000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:1.0000   1st Qu.:0.0000  
 Median :0.00000   Median :0.00000   Median :1.0000   Median :0.0000  
 Mean   :0.03424   Mean   :0.01514   Mean   :0.8882   Mean   :0.1118  
 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:1.0000   3rd Qu.:0.0000  
 Max.   :1.00000   Max.   :1.00000   Max.   :1.0000   Max.   :1.0000  
                                                                      
                  s1ecact                     s1eth      
 ilo employed         :9146   white              :12993  
 econ. inactive       :3444   asian groups       : 1005  
 ilo unemployed       :1724   black groups       :  260  
 not answered (9)     :   0   mixed/!other groups:  220  
 schedule not obtained:   0   refused/ns         :  184  
 (Other)              :   0   not answered (9)   :    0  
 NA's                 : 348   (Other)            :    0  
                     xq63a                          xq63b     
 not answered (9)       :   0   not answered (9)       :   0  
 schedule not obtained  :   0   schedule not obtained  :   0  
 schedule not applicable:   0   schedule not applicable:   0  
 item not applicable    :   0   item not applicable    :   0  
 agree                  :3815   agree                  :5762  
 disagree               :4583   disagree               :5733  
 NA's                   :6264   NA's                   :3167  
                     xq63c                           xq63d      
 not answered (9)       :    0   not answered (9)       :    0  
 schedule not obtained  :    0   schedule not obtained  :    0  
 schedule not applicable:    0   schedule not applicable:    0  
 item not applicable    :    0   item not applicable    :    0  
 agree                  : 1004   agree                  :10738  
 disagree               :12734   disagree               : 1885  
 NA's                   :  924   NA's                   : 2039  
                     xq63e     
 not answered (9)       :   0  
 schedule not obtained  :   0  
 schedule not applicable:   0  
 item not applicable    :   0  
 agree                  :9402  
 disagree               :3369  
 NA's                   :1891  
                                            sic                    s1ssr     
 whole-!sale, retail, hotels, transp-!ort, etc:5042   other south east:3319  
 public, educn., health, other comm., etc     :1010   north west      :1778  
 manif-!acturing, elect-!ricity, etc          : 594   west midlands   :1595  
 private!hh or! unclass-!ifiable              : 403   greater london  :1572  
 finance, real eatate, etc                    : 354   south west      :1423  
 (Other)                                      : 450   yorks & humber  :1256  
 NA's                                         :6809   (Other)         :3719  
                s1tec                     s1denom                   s1mret    
 kent              :  520   non denomiantional:10457   march 1998      :7245  
 devon and cornwall:  453   roman catholic    : 1451   april 1998      :5328  
 hampshire         :  436   church of england :  943   may 1998:       :1747  
 essex             :  434   other             :  851   june 1998       : 331  
 sussex            :  427   not applicable    :   51   unclear         :  11  
 (Other)           :11492   (Other)           :    9   not answered (9):   0  
 NA's              :  900   NA's              :  900   (Other)         :   0  
                 s1agej                     s1ages    
 not answered (99)  :   0   not answered (99)  :   0  
 item not applicable:   0   item not applicable:   0  
 16                 :9878   16                 :6081  
 17                 :4784   17                 :8579  
 unclear            :   0   unclear            :   2  
                                                      
                                                      
              s1leaua                                         s1voqu     
 cheshire (x)     :  716   none                                  :13261  
 dorset (x)       :  490   unknown level                         :  604  
 hampshire (x)    :  454   level 1                               :  406  
 essex (x)        :  432   level 2                               :  280  
 hertfordshire    :  335   level 1 (includes part one foundation):   46  
 staffordshire (x):  325   level 3                               :   35  
 (Other)          :11910   (Other)                               :   30  
                                                          s1avqu    
 level 2 (gnvq/nvq full award or 5+ gcses at a-c or 1 a-level:8532  
 level 1 (gnvq/nvq full award of 4 gcses any grade)          :5053  
 level unknown                                               : 498  
 below level 1 (nvq/gnvq certain units only, gnvq part i, 1-3: 295  
 none                                                        : 246  
 level 3 (gnvq/nvq full award or 2+ a-levels)                :  35  
 (Other)                                                     :   3  
                                                          s1peta    
 not answered (9)                                            :   0  
 item not applicable                                         :   0  
 5+ gcses at a*-c/inter. gnvq and 1+ gcses at a*-c/part one i:8832  
 1-4 gcses at a*-c/inter. gnvq/part one intermediate gnvq    :3579  
 5+ gcses at d-g/found'n gnvq and 1+ gcse at d-g/part one fou:1311  
 1-4 gcse at d-g/found'n gnvq/part one found'n gnvq          : 345  
 none                                                        : 595  
     s1a_c            s1d_g                             s1acqno    
 Min.   : 0.000   Min.   : 0.000   2+ a level (or equiv)    :6584  
 1st Qu.: 1.000   1st Qu.: 0.000   none/ns                  :6558  
 Median : 6.000   Median : 2.000   1-4 gcse                 : 911  
 Mean   : 5.298   Mean   : 2.847   1-1.5  a level (or equiv): 372  
 3rd Qu.: 9.000   3rd Qu.: 5.000   other academic           : 106  
 Max.   :13.000   Max.   :12.000   5+ gcse                  :  90  
                                   (Other)                  :  41  
                                    s1voqno               s1voqe     
 none                                   :9193   none         :12768  
 level 2                                :1990   unknown level:  656  
 level 3                                :1980   level 2      :  576  
 level 1                                : 634   level 1      :  557  
 unknown level (full & some units)      : 610   level 3      :   97  
 level 2 (includes part one itermediate): 197   level 4      :    8  
 (Other)                                :  58   (Other)      :    0  
                                                         s1hiqua    
 level 2 (gnvq/nvq full award or 5 gcses at a-c or 1 a level):8700  
 level 1(gnvq/nvq full award or 4 gcses any grade)           :4852  
 level unknown                                               : 463  
 less than level 1 (nvq/gnvq levels 1-4 certain units only, g: 289  
 none                                                        : 246  
 level 3 (gnvq/nvq full award or 2+ a levels)                : 104  
 (Other)                                                     :   8  
    s1a_cs1          s1d_gs1           s1mce       s1mce1        
 Min.   : 0.000   Min.   : 0.000   Min.   :0   Min.   :0.000000  
 1st Qu.: 2.000   1st Qu.: 0.000   1st Qu.:0   1st Qu.:0.000000  
 Median : 6.000   Median : 2.000   Median :0   Median :0.000000  
 Mean   : 5.329   Mean   : 2.866   Mean   :0   Mean   :0.003888  
 3rd Qu.: 9.000   3rd Qu.: 5.000   3rd Qu.:0   3rd Qu.:0.000000  
 Max.   :13.000   Max.   :14.000   Max.   :0   Max.   :1.000000  
                                                                 
     s1mce2             s1mce3            s1me       s1me01      
 Min.   :0.000000   Min.   :0.0000   Min.   :0   Min.   :0.0000  
 1st Qu.:0.000000   1st Qu.:1.0000   1st Qu.:0   1st Qu.:0.0000  
 Median :0.000000   Median :1.0000   Median :0   Median :1.0000  
 Mean   :0.005456   Mean   :0.9945   Mean   :0   Mean   :0.5444  
 3rd Qu.:0.000000   3rd Qu.:1.0000   3rd Qu.:0   3rd Qu.:1.0000  
 Max.   :1.000000   Max.   :1.0000   Max.   :0   Max.   :1.0000  
                                                                 
     s1me02           s1me03            s1me04            s1me05      
 Min.   :0.0000   Min.   :0.00000   Min.   :0.00000   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.0000  
 Median :0.0000   Median :0.00000   Median :0.00000   Median :0.0000  
 Mean   :0.4854   Mean   :0.04495   Mean   :0.01405   Mean   :0.1709  
 3rd Qu.:1.0000   3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.0000  
 Max.   :1.0000   Max.   :1.00000   Max.   :1.00000   Max.   :1.0000  
                                                                      
     s1me06            s1me07            s1me08            s1me09      
 Min.   :0.00000   Min.   :0.00000   Min.   :0.00000   Min.   :0.0000  
 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.0000  
 Median :0.00000   Median :0.00000   Median :0.00000   Median :0.0000  
 Mean   :0.08321   Mean   :0.05456   Mean   :0.03315   Mean   :0.2847  
 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:1.0000  
 Max.   :1.00000   Max.   :1.00000   Max.   :1.00000   Max.   :1.0000  
                                                                       
     s1me10            s1me11            s1me12          s1vqtp 
 Min.   :0.00000   Min.   :0.00000   Min.   :0.000   Min.   :0  
 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.000   1st Qu.:0  
 Median :0.00000   Median :0.00000   Median :0.000   Median :0  
 Mean   :0.07939   Mean   :0.07632   Mean   :0.129   Mean   :0  
 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.000   3rd Qu.:0  
 Max.   :1.00000   Max.   :1.00000   Max.   :1.000   Max.   :0  
                                                                
    s1vqtp01           s1vqtp02           s1vqtp03          s1vqtp04      
 Min.   :0.000000   Min.   :0.000000   Min.   :0.00000   Min.   :0.00000  
 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:0.00000  
 Median :0.000000   Median :0.000000   Median :0.00000   Median :0.00000  
 Mean   :0.007093   Mean   :0.003001   Mean   :0.01159   Mean   :0.00798  
 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.00000   3rd Qu.:0.00000  
 Max.   :1.000000   Max.   :1.000000   Max.   :1.00000   Max.   :1.00000  
                                                                          
    s1vqtp05           s1vqtp06          s1vqtp07           s1vqtp08       
 Min.   :0.000000   Min.   :0.00000   Min.   :0.000000   Min.   :0.000000  
 1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.000000  
 Median :0.000000   Median :0.00000   Median :0.000000   Median :0.000000  
 Mean   :0.003478   Mean   :0.02046   Mean   :0.002046   Mean   :0.003478  
 3rd Qu.:0.000000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.000000  
 Max.   :1.000000   Max.   :1.00000   Max.   :1.000000   Max.   :1.000000  
                                                                           
    s1vqtp09           s1vqtp10           s1vqtp11          s1vqtp12    
 Min.   :0.000000   Min.   :0.000000   Min.   :0.00000   Min.   :0.000  
 1st Qu.:0.000000   1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:1.000  
 Median :0.000000   Median :0.000000   Median :0.00000   Median :1.000  
 Mean   :0.002455   Mean   :0.001705   Mean   :0.02483   Mean   :0.919  
 3rd Qu.:0.000000   3rd Qu.:0.000000   3rd Qu.:0.00000   3rd Qu.:1.000  
 Max.   :1.000000   Max.   :1.000000   Max.   :1.00000   Max.   :1.000  
                                                                        
     s1gnvq         s1gnvq1         s1gnvq2         s1gnvq3     
 Min.   :0       Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0       1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :0       Median :0.000   Median :0.000   Median :0.000  
 Mean   :0       Mean   :0.075   Mean   :0.442   Mean   :0.387  
 3rd Qu.:0       3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:1.000  
 Max.   :0       Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :12232   NA's   :12232   NA's   :12232   NA's   :12232  
    s1gnvq4         s1gnvq5         s1gnvq6         s1gnvq7     
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :0.000   Median :0.000   Median :0.000   Median :0.000  
 Mean   :0.016   Mean   :0.049   Mean   :0.011   Mean   :0.027  
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:0.000  
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :12232   NA's   :12232   NA's   :12232   NA's   :12232  
     s1nvq          s1nvq01         s1nvq02         s1nvq03     
 Min.   :0       Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0       1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :0       Median :0.000   Median :1.000   Median :0.000  
 Mean   :0       Mean   :0.174   Mean   :0.565   Mean   :0.218  
 3rd Qu.:0       3rd Qu.:0.000   3rd Qu.:1.000   3rd Qu.:0.000  
 Max.   :0       Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :12869   NA's   :12869   NA's   :12869   NA's   :12869  
    s1nvq04         s1nvq05         s1nvq06         s1nvq07     
 Min.   :0.000   Min.   :0.000   Min.   :0.000   Min.   :0.000  
 1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000   1st Qu.:0.000  
 Median :0.000   Median :0.000   Median :0.000   Median :0.000  
 Mean   :0.099   Mean   :0.028   Mean   :0.064   Mean   :0.018  
 3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:0.000   3rd Qu.:0.000  
 Max.   :1.000   Max.   :1.000   Max.   :1.000   Max.   :1.000  
 NA's   :12869   NA's   :12869   NA's   :12869   NA's   :12869  
    s1nvq08         s1nvq09          s1payh          s1payho      
 Min.   :0.00    Min.   :0.00    Min.   :  0.02   Min.   :  0.25  
 1st Qu.:0.00    1st Qu.:0.00    1st Qu.:  2.16   1st Qu.:  1.50  
 Median :0.00    Median :0.00    Median :  2.88   Median :  2.08  
 Mean   :0.03    Mean   :0.06    Mean   : 15.87   Mean   : 32.30  
 3rd Qu.:0.00    3rd Qu.:0.00    3rd Qu.:  3.50   3rd Qu.:  2.89  
 Max.   :1.00    Max.   :1.00    Max.   :997.00   Max.   :997.00  
 NA's   :12869   NA's   :12869   NA's   :7318     NA's   :14228   
                   s1apr97                        s1may97     
 ft edn                :10588   ft edn                :10381  
 not answered          : 1723   not answered          : 1677  
 out of work/unemployed:  911   out of work/unemployed:  916  
 something else        :  529   something else        :  600  
 pt job                :  468   pt job                :  560  
 ft job                :  304   ft job                :  364  
 (Other)               :  139   (Other)               :  164  
                   s1jun97                       s1jul97    
 ft edn                :8904   ft edn                :4813  
 not answered          :1552   pt job                :2452  
 out of work/unemployed:1117   something else        :2392  
 pt job                :1076   out of work/unemployed:1627  
 something else        :1000   not answered          :1549  
 ft job                : 651   ft job                :1202  
 (Other)               : 362   (Other)               : 627  
                   s1aug97                       s1sep97     
 ft edn                :3684   ft edn                :10958  
 pt job                :2871   gst                   : 1123  
 something else        :2699   ft job                :  993  
 out of work/unemployed:1610   pt job                :  506  
 not answered          :1559   out of work/unemployed:  496  
 ft job                :1404   not answered          :  324  
 (Other)               : 835   (Other)               :  262  
                   s1oct97                        s1nov97     
 ft edn                :11365   ft edn                :11300  
 gst                   : 1166   gst                   : 1177  
 ft job                : 1016   ft job                : 1076  
 out of work/unemployed:  407   out of work/unemployed:  415  
 pt job                :  324   pt job                :  333  
 not answered          :  260   not answered          :  241  
 (Other)               :  124   (Other)               :  120  
                   s1dec97                        s1jan98     
 ft edn                :11105   ft edn                :11038  
 gst                   : 1185   gst                   : 1221  
 ft job                : 1106   ft job                : 1159  
 out of work/unemployed:  470   out of work/unemployed:  524  
 pt job                :  376   pt job                :  334  
 not answered          :  249   not answered          :  235  
 (Other)               :  171   (Other)               :  151  
                   s1feb98     
 ft edn                :10962  
 gst                   : 1241  
 ft job                : 1218  
 out of work/unemployed:  532  
 pt job                :  339  
 not answered          :  219  
 (Other)               :  151  

Various WARNINGS will appear. Don't panic.

To see the summary of the data use the scroll bar to scroll down.


Get a subset of the data with only the variables needed.

In [11]:
myvars <- c("serial", "weight", "sex", "s1a_c", "a58", "s1eth", "s1acqe", "pseg", "pseg1", "pseg2", "pseg3", "pseg4", "pseg5", "pseg6", "pseg7")
mydata.df <- mydata.df[myvars]
In [6]:
summary(mydata.df)
Out[6]:
     serial           weight                        sex           s1a_c       
 Min.   :200001   Min.   :0.6025   not answered (9)   :   0   Min.   : 0.000  
 1st Qu.:206123   1st Qu.:0.7661   item not applicable:   0   1st Qu.: 1.000  
 Median :211589   Median :0.8779   male               :6889   Median : 6.000  
 Mean   :212056   Mean   :1.0000   female             :7773   Mean   : 5.298  
 3rd Qu.:217027   3rd Qu.:1.0576                              3rd Qu.: 9.000  
 Max.   :231392   Max.   :2.5176                              Max.   :13.000  
                                                                              
                  a58                        s1eth      
 white              :12993   white              :12993  
 indian             :  436   asian groups       : 1005  
 pakistani          :  280   black groups       :  260  
 mixed ethnic origin:  126   mixed/!other groups:  220  
 bangladeshi        :  112   refused/ns         :  184  
 (Other)            :  544   not answered (9)   :    0  
 NA's               :  171   (Other)            :    0  
               s1acqe          pseg       pseg1            pseg2       
 5+ gcses at a*-c :8465   Min.   :0   Min.   :0.0000   Min.   :0.0000  
 1-4 gcses at a*-c:3676   1st Qu.:0   1st Qu.:0.0000   1st Qu.:0.0000  
 5+ gcses at d-g  :1448   Median :0   Median :0.0000   Median :0.0000  
 none reported    : 745   Mean   :0   Mean   :0.2299   Mean   :0.2064  
 1-4 gcses at d-g : 328   3rd Qu.:0   3rd Qu.:0.0000   3rd Qu.:0.0000  
 not answered (9) :   0   Max.   :0   Max.   :1.0000   Max.   :1.0000  
 (Other)          :   0                                                
     pseg3            pseg4           pseg5             pseg6         
 Min.   :0.0000   Min.   :0.000   Min.   :0.00000   Min.   :0.000000  
 1st Qu.:0.0000   1st Qu.:0.000   1st Qu.:0.00000   1st Qu.:0.000000  
 Median :0.0000   Median :0.000   Median :0.00000   Median :0.000000  
 Mean   :0.3141   Mean   :0.108   Mean   :0.03581   Mean   :0.003819  
 3rd Qu.:1.0000   3rd Qu.:0.000   3rd Qu.:0.00000   3rd Qu.:0.000000  
 Max.   :1.0000   Max.   :1.000   Max.   :1.00000   Max.   :1.000000  
                                                                      
     pseg7       
 Min.   :0.0000  
 1st Qu.:0.0000  
 Median :0.0000  
 Mean   :0.1019  
 3rd Qu.:0.0000  
 Max.   :1.0000  
                 

str compactly display the internal structure of an R object.

It is a diagnostic function and an alternative to summary.

In [12]:
str(mydata.df)
'data.frame':	14662 obs. of  15 variables:
 $ serial: int  200001 200004 200005 200006 200008 200012 200013 200014 200019 200022 ...
 $ weight: num  0.875 0.976 0.976 0.976 1.841 ...
 $ sex   : Factor w/ 4 levels "not answered (9)",..: 4 3 3 3 4 4 4 4 3 4 ...
 $ s1a_c : int  9 9 9 9 0 1 5 2 1 1 ...
 $ a58   : Factor w/ 15 levels "not answered (99)",..: 4 4 8 4 6 11 6 4 10 10 ...
 $ s1eth : Factor w/ 9 levels "not answered (9)",..: 5 5 7 5 6 7 6 5 7 7 ...
 $ s1acqe: Factor w/ 9 levels "not answered (9)",..: 5 5 5 5 7 6 5 6 6 6 ...
 $ pseg  : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg1 : int  1 0 0 0 0 0 0 0 0 0 ...
 $ pseg2 : int  0 1 0 1 0 0 0 0 0 0 ...
 $ pseg3 : int  0 0 1 0 0 0 0 1 0 0 ...
 $ pseg4 : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg5 : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg6 : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg7 : int  0 0 0 0 1 1 1 0 1 1 ...

View the data in spreadsheet format.

In [13]:
head(mydata.df)
Out[13]:
serialweightsexs1a_ca58s1eths1acqepsegpseg1pseg2pseg3pseg4pseg5pseg6pseg7
12000010.87518female9whitewhite5+ gcses at a*-c01000000
22000040.97615male9whitewhite5+ gcses at a*-c00100000
32000050.97615male9indianasian groups5+ gcses at a*-c00010000
42000060.97615male9whitewhite5+ gcses at a*-c00100000
52000081.84073female0afro.black groups5+ gcses at d-g00000001
62000120.95928female1chin!eseasian groups1-4 gcses at a*-c00000001

Construct the outcome variable

The binary indicator of 5+ GCSEs A (star) - C will be "s15a_c" .

It is constructed from variable "s1a_c" - the number of GCSEs A (star) - C.

Tabulate the original outcome "s1a_c" number of GCSEs A (star) - C .

In [14]:
table(mydata.df$s1a_c)
Out[14]:
   0    1    2    3    4    5    6    7    8    9   10   11   12   13 
2538 1138  936  833  802  788  854 1023 1373 2459 1525  345   45    3 

Construct the binary outcome variable "s15a_c" 5+ GCSEs at grades A-C

Following the existing naming convention used in YCS Cohort 9 I have chosen the title "s15a_c" because this is a sweep 1 measure "s1" of 5+ GCSEs at grades A-C "5a_c" hence "s15a_c".

Create the "empty" new field.

In [15]:
mydata.df$s15a_c <- NA
table(mydata.df$s15a_c)
Out[15]:
< table of extent 0 >

The new field "$s15a_c" is empty.

Recode the old field into the new one for the specified rows.

In [16]:
mydata.df$s15a_c[mydata.df$s1a_c>4] <-1
table(mydata.df$s15a_c)

mydata.df$s15a_c[mydata.df$s1a_c<5] <-0
table(mydata.df$s15a_c)
Out[16]:
   1 
8415 
Out[16]:
   0    1 
6247 8415 

Construct the first variable explanatory variable girls (gender)

The binary indicator of girls (gender) from the existing variable "sex" .

This is a factor. Therefore I will check levels in the original data boys==1 and girls==2.

In [17]:
levels(mydata.df$sex)
table (mydata.df$sex)
Out[17]:
  1. "not answered (9)"
  2. "item not applicable"
  3. "male"
  4. "female"
Out[17]:
   not answered (9) item not applicable                male              female 
                  0                   0                6889                7773 

Create the "empty" new field.

In [18]:
# create the new field
mydata.df$girls <- NA
table(mydata.df$girls)
Out[18]:
< table of extent 0 >

The new field "$girls" is empty.

Recode the old field into the new one for the specified rows.

In [19]:
mydata.df$girls[mydata.df$sex=="male"] <-0
mydata.df$girls[mydata.df$sex=="female"] <-1
In [20]:
table(mydata.df$girls)
Out[20]:
   0    1 
6889 7773 

Construct the explanatory variable for ethnicity

Beware this measure is messy!

This is a factor. Therefore I check levels in the original data.

In [21]:
levels(mydata.df$a58)
Out[21]:
  1. "not answered (99)"
  2. "don't know (98)"
  3. "item not applicable"
  4. "white"
  5. "carib."
  6. "afro."
  7. "other black"
  8. "indian"
  9. "pakistani"
  10. "bangladeshi"
  11. "chin!ese"
  12. "other asian"
  13. "any other"
  14. "mixed ethnic origin"
  15. "ref!used"

Now I create a table of the ethnicity measure "a58".

In [14]:
table(mydata.df$a58)
Out[14]:
  not answered (99)     don't know (98) item not applicable               white 
                  0                   0                   0               12993 
             carib.               afro.         other black              indian 
                104                  78                  78                 436 
          pakistani         bangladeshi            chin!ese         other asian 
                280                 112                  78                  99 
          any other mixed ethnic origin            ref!used 
                 94                 126                  13 

These are the dummies that are required for the model in Connolly (2006, p.20)

Chinese
Indian
White
Bangladeshi
Pakistani

Strangely, the "Other" category is not in the model!


Ethnic categories required for the analysis.

These are the categories developed and used in Connolly (2006) Table 1 (p.7)

White Indian Pakistani Black Bangladeshi Chinese Other

Here are the labels and codes in the YCS dataset

  • 1 "white"
  • 2 "carib." "afro." "other black"
  • 3 "indian"
  • 4 "pakistani"
  • 5 "bangladeshi"
  • 6 "chin!ese"
  • 7 "other asian"
  • 10 "any other"
  • 97 "mixed ethnic origin"
  • . "ref!used"

Here are my estimates of the number is each ethnic category used in Connolly (2006) Table 1 (p.7)

1 White 12993
2 Black 260
3 Indian 436
4 Pakistani 280
5 Bangladeshi 112
6 Chinese 78
7 Other 503

Create the new field "ethnic1".

Everyone is placed into category 7.

I then recode the new field "ethnic1" with values from "a58" .

There is an explanation of this unorthodox approach below...

In [23]:
# create the new field,

mydata.df$ethnic1 <- 7

# everyone is placed into category 7.

# recode the new field with values from the old field.
mydata.df$ethnic1[mydata.df$a58=="white"] <-1
mydata.df$ethnic1[mydata.df$a58=="carib."] <-2
mydata.df$ethnic1[mydata.df$a58=="afro."] <-2
mydata.df$ethnic1[mydata.df$a58=="other black"] <-2
mydata.df$ethnic1[mydata.df$a58=="indian"] <-3
mydata.df$ethnic1[mydata.df$a58=="pakistani"] <-4
mydata.df$ethnic1[mydata.df$a58=="bangladeshi"] <-5
mydata.df$ethnic1[mydata.df$a58=="chin!ese"] <-6
mydata.df$ethnic1[mydata.df$a58=="other asian"] <-7
mydata.df$ethnic1[mydata.df$a58=="any other"] <-7
mydata.df$ethnic1[mydata.df$a58=="mixed ethnic origin"] <-7
mydata.df$ethnic1[mydata.df$a58=="ref!used"] <-7

There appears to be a quirk in the labelling of the missing values "." in the Stata file.

I have got around this by forcing these cases into category 7 when I created the new field
i.e. mydata.df$ethnic1 <- 7

Create a table of the new "ethnic1" variable.

In [24]:
table(mydata.df$ethnic1)
Out[24]:
    1     2     3     4     5     6     7 
12993   260   436   280   112    78   503 

This might not be the neatest solution! But the obstactle has been overcome.

In [25]:
# Just to check the variable again.

table(mydata.df$ethnic1)
Out[25]:
    1     2     3     4     5     6     7 
12993   260   436   280   112    78   503 
In [26]:
# Double check ethnic1 is not a factor

levels(mydata.df$ethnic1)
Out[26]:
NULL

Construct a series of dummy variables for ethnicity

I have chosen to construct a each variable manually, in order to double check it.

White pupils.

In [27]:
mydata.df$white <-0
table(mydata.df$white)
mydata.df$white[mydata.df$ethnic1=="1"] <-1
table(mydata.df$white)
Out[27]:
    0 
14662 
Out[27]:
    0     1 
 1669 12993 

Black pupils.

In [28]:
mydata.df$black <-0
table(mydata.df$black)
mydata.df$black[mydata.df$ethnic1=="2"] <-1
table(mydata.df$black)
Out[28]:
    0 
14662 
Out[28]:
    0     1 
14402   260 

Indian pupils

In [29]:
mydata.df$indian <-0
table(mydata.df$indian)
mydata.df$indian[mydata.df$ethnic1=="3"] <-1
table(mydata.df$indian)
Out[29]:
    0 
14662 
Out[29]:
    0     1 
14226   436 

Pakistani pupils.

In [30]:
mydata.df$pakistani <-0
table(mydata.df$pakistani)
mydata.df$pakistani[mydata.df$ethnic1=="4"] <-1
table(mydata.df$pakistani)
Out[30]:
    0 
14662 
Out[30]:
    0     1 
14382   280 

Bangladeshi pupils.

In [31]:
mydata.df$bangladeshi <-0
table(mydata.df$bangladeshi)
mydata.df$bangladeshi[mydata.df$ethnic1=="5"] <-1
table(mydata.df$bangladeshi)
Out[31]:
    0 
14662 
Out[31]:
    0     1 
14550   112 

Chinese pupils.

In [32]:
mydata.df$chinese <-0
table(mydata.df$chinese)
mydata.df$chinese[mydata.df$ethnic1=="6"] <-1
table(mydata.df$chinese)
Out[32]:
    0 
14662 
Out[32]:
    0     1 
14584    78 

Other pupils.

In [33]:
mydata.df$other <-0
table(mydata.df$other)
mydata.df$other[mydata.df$ethnic1=="7"] <-1
table(mydata.df$other)
Out[33]:
    0 
14662 
Out[33]:
    0     1 
14159   503 

The block of dummy variables representing ethnicity have been constructed.

Now I perform a brief test.

Here is a table of the outcome variable 5+ GCSEs at grades A - C.

In [34]:
table(mydata.df$s15a_c)
Out[34]:
   0    1 
6247 8415 

Here is a table of ethnicity.

In [35]:
table(mydata.df$ethnic1)
Out[35]:
    1     2     3     4     5     6     7 
12993   260   436   280   112    78   503 

Here is a table of school GCSE outcome by ethnicity

In [36]:
mytable <- table(mydata.df$ethnic1, mydata.df$s15a_c) # A will be rows, B will be columns 
mytable # print table
Out[36]:
   
       0    1
  1 5433 7560
  2  158  102
  3  160  276
  4  172  108
  5   64   48
  6   20   58
  7  240  263

There results look plausible and I am happy that the measures are behaving themselves.


Construct the explanatory variable for social class

Beware this a bit messy!

The variables pseg1 - pseg7 are social class dummies.

I would like these variables to have names that are more "human-eye-readable".


Here is the first social class dummy "pseg1" which is the Professional/Managerial social class.

In [43]:
table(mydata.df$pseg1)
Out[43]:
< table of extent 0 >

Here we will be using the reshape library.

Make sure that it has been installed make sure that it has been installed

The R code is
install.packages ("reshape")

In [42]:
library(reshape)

Various WARNINGS might appear. Don't panic.

Here is the code to rename "pseg1" as "prof_man" i.e.

In [ ]:
mydata.df <- rename(mydata.df, c(pseg1="prof_man"))

Now take a look at the "renamed" variable.

In [44]:
table(mydata.df$prof_man)
Out[44]:
    0     1 
11291  3371 

I now rename pseg2 - pseg4.

In [46]:
mydata.df <- rename(mydata.df, c(pseg2="o_non_man"))
table(mydata.df$o_non_man)
Out[46]:
    0     1 
11636  3026 
In [85]:
mydata.df <- rename(mydata.df, c(pseg3="skilled_man"))
table(mydata.df$skilled_man)
Out[85]:
    0     1 
10056  4606 
In [84]:
mydata.df <- rename(mydata.df, c(pseg4="semi_skilled"))
table(mydata.df$semi_skilled)
Out[84]:
    0     1 
13078  1584 

The dataset has now been 'wrangled' or 'enabled' and should be in reasonable shape to test.

In the next stage I test the data and ultimately I will try to duplicate the model in Connelly (2006, p.20).

Now I save the wrangled data frame in a file called ycs9sw1.rda.

In [87]:
save(mydata.df,file="C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1.rda")

List the objects in my workspace.

In [88]:
ls()
Out[88]:
  1. "mydata.df"
  2. "mydesign1"
  3. "small.w"

Now I am going to remove "rm" these objects.

In [89]:
rm ("mydata.df", "mytable", "myvars")
ls()
Warning message:
In rm("mydata.df", "mytable", "myvars"): object 'mytable' not foundWarning message:
In rm("mydata.df", "mytable", "myvars"): object 'myvars' not found
Out[89]:
  1. "mydesign1"
  2. "small.w"

Data Test

In this section I undertake a small series of exploratory data analysis tasks to check the data with the published results in Connolly (2006).


Re-loading the data frame from the saved file.

In [92]:
load("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1.rda")
ls()
Out[92]:
"mydata.df"

Now I set up the survey desing of the YCS 9.

Within an object called "small.w" I specify the design.

The "ids" are the identification for each case i.e. "serial".
The data are "mydata.df".
The survey weights are "weight".

In [93]:
small.w <- svydesign(ids = ~serial, data = mydata.df, weights = ~weight)

Now I attempt to check the values of my variables against the values (n) and proportions reported in Connolly (2006, p.7, Table 1).

Q-Step_Slide


Girls.

In [96]:
table(svytable(~girls, design = small.w))
prop.table(svytable(~girls, design = small.w))
Out[96]:
7268.86727  7393.1375 
         1          1 
Out[96]:
girls
        0         1 
0.5042378 0.4957622 

These results are correct. Checked with Connolly (2006, p.7, Table 1).


Ethnicity.

In [97]:
table(svytable(~ethnic1, design = small.w))
prop.table(svytable(~ethnic1, design = small.w))
Out[97]:
   74.05745   122.49261   297.11676   311.67752    437.4739   525.13248 
          1           1           1           1           1           1 
12894.05405 
          1 
Out[97]:
ethnic1
          1           2           3           4           5           6 
0.879419578 0.020264402 0.029837250 0.021257497 0.008354424 0.005050977 
          7 
0.035815872 

These results are correct. Checked with Connolly (2006, p.7, Table 1).

Remember that the ordering in Connolly (2006, p.7, Table 1) is not the same as in the logit model Connolly (2006, p.20).


Social class.

Here I remind myself of the variable names.

I use str which is a compact display of the "structure" of an arbitrary R object.

In [98]:
str(mydata.df)
'data.frame':	14662 obs. of  25 variables:
 $ serial      : int  200001 200004 200005 200006 200008 200012 200013 200014 200019 200022 ...
 $ weight      : num  0.875 0.976 0.976 0.976 1.841 ...
 $ sex         : Factor w/ 4 levels "not answered (9)",..: 4 3 3 3 4 4 4 4 3 4 ...
 $ s1a_c       : int  9 9 9 9 0 1 5 2 1 1 ...
 $ a58         : Factor w/ 15 levels "not answered (99)",..: 4 4 8 4 6 11 6 4 10 10 ...
 $ s1eth       : Factor w/ 9 levels "not answered (9)",..: 5 5 7 5 6 7 6 5 7 7 ...
 $ s1acqe      : Factor w/ 9 levels "not answered (9)",..: 5 5 5 5 7 6 5 6 6 6 ...
 $ pseg        : int  0 0 0 0 0 0 0 0 0 0 ...
 $ prof_man    : int  1 0 0 0 0 0 0 0 0 0 ...
 $ o_non_man   : int  0 1 0 1 0 0 0 0 0 0 ...
 $ skilled_man : int  0 0 1 0 0 0 0 1 0 0 ...
 $ semi_skilled: int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg5       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg6       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg7       : int  0 0 0 0 1 1 1 0 1 1 ...
 $ s15a_c      : num  1 1 1 1 0 0 1 0 0 0 ...
 $ girls       : num  1 0 0 0 1 1 1 1 0 1 ...
 $ ethnic1     : num  1 1 3 1 2 6 2 1 5 5 ...
 $ white       : num  1 1 0 1 0 0 0 1 0 0 ...
 $ black       : num  0 0 0 0 1 0 1 0 0 0 ...
 $ indian      : num  0 0 1 0 0 0 0 0 0 0 ...
 $ pakistani   : num  0 0 0 0 0 0 0 0 0 0 ...
 $ bangladeshi : num  0 0 0 0 0 0 0 0 1 1 ...
 $ chinese     : num  0 0 0 0 0 1 0 0 0 0 ...
 $ other       : num  0 0 0 0 0 0 0 0 0 0 ...
In [105]:
print("prof_man")
table(svytable(~prof_man , design = small.w))
prop.table(svytable(~prof_man , design = small.w))

print("o_non_man")
table(svytable(~o_non_man , design = small.w))
prop.table(svytable(~o_non_man , design = small.w))

print("skilled_man")
table(svytable(~skilled_man, design = small.w))
prop.table(svytable(~skilled_man , design = small.w))

print("semi_skilled")
table(svytable(~semi_skilled , design = small.w))
prop.table(svytable(~semi_skilled , design = small.w))
[1] "prof_man"
Out[105]:
 3048.57466 11613.43011 
          1           1 
Out[105]:
prof_man
        0         1 
0.7920765 0.2079235 
[1] "o_non_man"
Out[105]:
  2829.6733 11832.33147 
          1           1 
Out[105]:
o_non_man
        0         1 
0.8070064 0.1929936 
[1] "skilled_man"
Out[105]:
4697.93136 9964.07341 
         1          1 
Out[105]:
skilled_man
        0         1 
0.6795847 0.3204153 
[1] "semi_skilled"
Out[105]:
 1702.20359 12959.80118 
          1           1 
Out[105]:
semi_skilled
        0         1 
0.8839038 0.1160962 

These results are correct.

Checked with Connolly (2006, p.7, Table 1).

Remember that the categories used in the logit model Connolly (2006, p.20). are not the same as in Connolly (2006, p.7, Table 1).


In this section I have undertaken a small series of exploratory data analysis tasks to check the data with the published results in Connolly (2006).

I am confident that the data are in good shape ready for duplicating the logit model.


Data Analysis

Duplicating the Connelly (2006) Model Results in R

Table 5 p.20 Connolly (2006).

Q-Step_Slide


Beware if you skipped to this section then make sure that you have the correct data frame (i.e. the data file "ycs9sw1.rda").

Re-loading the data frame from the saved file requries this R code

_load("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_92017/ycs9sw1.rda")
ls()

It is currently in the markdown cell below.

You might also require the R libraries.

Setting up the survey design of the YCS data.

In [3]:
library(foreign)
library(survey)
library(car)
library(dplyr)
library(weights)
library(dummies)
load("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1.rda")
ls()
Warning message:
: package 'survey' was built under R version 3.2.5Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Warning message:
: package 'survival' was built under R version 3.2.5
Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

Warning message:
: package 'car' was built under R version 3.2.5Warning message:
: package 'dplyr' was built under R version 3.2.5
Attaching package: 'dplyr'

The following object is masked from 'package:car':

    recode

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Warning message:
: package 'weights' was built under R version 3.2.5Loading required package: Hmisc
Warning message:
: package 'Hmisc' was built under R version 3.2.5Loading required package: lattice
Loading required package: Formula
Warning message:
: package 'Formula' was built under R version 3.2.5Loading required package: ggplot2
Warning message:
: package 'ggplot2' was built under R version 3.2.5
Error: package 'ggplot2' could not be loaded
Warning message:
: package 'dummies' was built under R version 3.2.5dummies-1.5.6 provided by Decision Patterns

Out[3]:
  1. "mydata.df"
  2. "mydata4.df"
In [2]:
mydesign1 <- svydesign(id = ~serial,data = mydata.df, weight = ~weight)

This is a svy (i.e.survey) logit regression model.
The outcome variable is "s15a_c" - 5+ GCSEs at grades A - C .

The explanatory variables are

girls
ethnicity (represented by a block of dummy variables)
social class (represented by a block of dummy variables).

In [3]:
model1<-svyglm (s15a_c ~ girls + chinese + indian +
                 white + bangladeshi + pakistani + 
                 pakistani + prof_man + o_non_man + 
                 skilled_man + semi_skilled, design=mydesign1, data = mydata.df, family = "binomial")
Warning message:
In eval(expr, envir, enclos): non-integer #successes in a binomial glm!

There might be a warning message because we are modelling survey (i.e. weighted) data.
Don't panic.

Summary of the model results.

In [4]:
summary (model1)
Out[4]:
Call:
svyglm(formula = s15a_c ~ girls + chinese + indian + white + 
    bangladeshi + pakistani + pakistani + prof_man + o_non_man + 
    skilled_man + semi_skilled, design = mydesign1, data = mydata.df, 
    family = "binomial")

Survey design:
svydesign(id = ~serial, data = mydata.df, weight = ~weight)

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  -1.58272    0.09190 -17.223  < 2e-16 ***
girls         0.39532    0.03663  10.791  < 2e-16 ***
chinese       1.34282    0.29745   4.514 6.40e-06 ***
indian        0.60915    0.13734   4.435 9.26e-06 ***
white         0.16152    0.08575   1.884   0.0596 .  
bangladeshi   0.24018    0.21983   1.093   0.2746    
pakistani    -0.06046    0.15696  -0.385   0.7001    
prof_man      2.04847    0.06612  30.980  < 2e-16 ***
o_non_man     1.62986    0.06503  25.062  < 2e-16 ***
skilled_man   0.79762    0.05867  13.595  < 2e-16 ***
semi_skilled  0.43251    0.07230   5.982 2.25e-09 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1.000384)

Number of Fisher Scoring iterations: 4

These results are not the same as the results presented in Table 5, p.20 Connolly (2006).

The difference may not be immediately apparent.

In the published work Connelly (2006)

a) the pupils in ethnic category "other" are dropped from the analysis

b) the pupils in class categories "other" and "unclassified" are dropped from the analysis.


Here we subset ethnic categories 1 - 6.

In [8]:
table(mydata.df$ethnic1)
Out[8]:
    1     2     3     4     5     6     7 
12993   260   436   280   112    78   503 

Here we subset ethnic categories 1 - 6.

In [7]:
mydata2.df <- subset(mydata.df, ethnic1!=7)
table(mydata.df$ethnic1)
table(mydata2.df$ethnic1)
Out[7]:
    1     2     3     4     5     6     7 
12993   260   436   280   112    78   503 
Out[7]:
    1     2     3     4     5     6 
12993   260   436   280   112    78 

Here we subset pupils in class categories pseg1 - pseg5.

In [8]:
table(mydata2.df$pseg6)
table(mydata2.df$pseg7)
Out[8]:
    0     1 
14106    53 
Out[8]:
    0     1 
12842  1317 
In [9]:
mydata3.df <- subset(mydata2.df, pseg6!=1)
table(mydata.df$pseg6)
table(mydata3.df$pseg6)
Out[9]:
    0     1 
14606    56 
Out[9]:
    0 
14106 
In [10]:
mydata4.df <- subset(mydata3.df, pseg7!=1)
table(mydata.df$pseg7)
table(mydata4.df$pseg7)
Out[10]:
    0     1 
13168  1494 
Out[10]:
    0 
12789 

The dataset should be in shape now for estimating the (survey) logit model.


Beware you might need to reset the design.

In [19]:
mydesign2 <- svydesign(id = ~serial,data = mydata4.df, weight = ~weight)
In [22]:
model2<-svyglm (s15a_c ~ girls + chinese + indian +
                 white + bangladeshi + pakistani + 
                 pakistani + prof_man + o_non_man + 
                 skilled_man + semi_skilled, design=mydesign2, data = mydata4.df, family = "binomial")
Warning message:
In eval(expr, envir, enclos): non-integer #successes in a binomial glm!

There might be a warning message because we are modelling survey (i.e. weighted) data.
Don't panic.

Summary of the model results.

In [23]:
summary (model2)
Out[23]:
Call:
svyglm(formula = s15a_c ~ girls + chinese + indian + white + 
    bangladeshi + pakistani + pakistani + prof_man + o_non_man + 
    skilled_man + semi_skilled, design = mydesign2, data = mydata4.df, 
    family = "binomial")

Survey design:
svydesign(id = ~serial, data = mydata4.df, weight = ~weight)

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  -2.20829    0.19802 -11.152  < 2e-16 ***
girls         0.40456    0.03926  10.305  < 2e-16 ***
chinese       2.00231    0.37734   5.306 1.14e-07 ***
indian        1.06584    0.20829   5.117 3.15e-07 ***
white         0.64314    0.17118   3.757 0.000173 ***
bangladeshi   0.76616    0.34486   2.222 0.026323 *  
pakistani     0.53136    0.24503   2.169 0.030135 *  
prof_man      2.19209    0.10863  20.179  < 2e-16 ***
o_non_man     1.77251    0.10793  16.423  < 2e-16 ***
skilled_man   0.93217    0.10411   8.954  < 2e-16 ***
semi_skilled  0.57587    0.11264   5.112 3.23e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1.000269)

Number of Fisher Scoring iterations: 4

These results are now the same as in the published model

Q-Step_Slide

I now save the (latest) data frame as a file "ycs9sw1_v2.rda".

In [25]:
save(mydata4.df,file="C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.rda")

List the objects in my workspace.

In [26]:
ls()
Out[26]:
  1. "model1"
  2. "model2"
  3. "mydata.df"
  4. "mydata2.df"
  5. "mydata3.df"
  6. "mydata4.df"
  7. "mydesign1"
  8. "mydesign2"

Now I am going to remove "rm" these objects.

In [27]:
rm ("mydata.df", "mydata2.df", "mydata3.df", "model1", "mydesign1")
ls()
Out[27]:
  1. "model2"
  2. "mydata4.df"
  3. "mydesign2"

Duplicating the Connelly (2006) Model Results in SPSS

A close look at the results of the model in R indicate that whilst the values of the parameter estimates "estimates" are the same as B in Table 5 (p.20) the standard errors are not the same.

My intuition is that the original analysis was undertaken in SPSS.

This is an unforeseen obstacle.

My desire is to investigate this a little further.

Unfortunately, at the current time there is not a SPSS kernel available within the Jupyter notebook.

However, I have a cunning plan.

First, I will write out the dataset in SPSS format.

write.foreign doesn't generate native SPSS datafiles (.sav) but it does generate is the data in a comma delimited format (a .txt file) and a basic syntax file for reading that data into SPSS (a .sps file).

Using the following general syntax

write.foreign(as.data.frame(mydata), "c:/mydata.txt", "c:/mydata.sps", package="SPSS")

I plan to estimate the logit model in SPSS (with the data weighted).

In [28]:
write.foreign(as.data.frame(mydata4.df), "C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.txt", "C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.sps", package="SPSS")
Warning message:
In writeForeignSPSS(df = structure(list(serial = c(200001L, 200004L, : some variable names were abbreviated

Here we leave the Jupyter notebook

We have had to break the workflow because SPSS cannot currently be run in the language agnostic environment of the Jupyter notebook.

To assist with transparency this link shows the model being estimated in SPSS
(IBM SPSS Version 22 Release 22.0.0.1 64-bit)

https://youtu.be/12YXww67m9s

I am grateful to Dr Roxanne Connelly, University of Warwick, UK (http://www2.warwick.ac.uk/fac/soc/sociology/staff/connelly/) for this suggestion.

I use the following on-line software to record the SPSS job https://www.apowersoft.com/free-online-screen-recorder .

Here is the SPSS syntax that was generated by the write.foreign command.


DATA LIST FILE= "C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.txt" free (",") / serial weight sex s1a_c a58 s1eth s1acqe pseg prof_man o_non_mn sklld_mn sm_sklld pseg5 pseg6 pseg7 s15a_c girls ethnic1 white black indian pakistan bangldsh chinese other .

VARIABLE LABELS serial "serial" weight "weight" sex "sex" s1a_c "s1a_c" a58 "a58" s1eth "s1eth" s1acqe "s1acqe" pseg "pseg" prof_man "prof_man" o_non_mn "o_non_man" sklld_mn "skilled_man" sm_sklld "semi_skilled" pseg5 "pseg5" pseg6 "pseg6" pseg7 "pseg7" s15a_c "s15a_c" girls "girls" ethnic1 "ethnic1" white "white" black "black" indian "indian" pakistan "pakistani" bangldsh "bangladeshi" chinese "chinese" other "other" .

VALUE LABELS / sex 1 "not answered (9)" 2 "item not applicable" 3 "male" 4 "female" / a58 1 "not answered (99)" 2 "don't know (98)" 3 "item not applicable" 4 "white" 5 "carib." 6 "afro." 7 "other black" 8 "indian" 9 "pakistani" 10 "bangladeshi" 11 "chin!ese" 12 "other asian" 13 "any other" 14 "mixed ethnic origin" 15 "ref!used" / s1eth 1 "not answered (9)" 2 "schedule not obtained" 3 "schedule not applicable" 4 "item not applicable" 5 "white" 6 "black groups" 7 "asian groups" 8 "mixed/!other groups" 9 "refused/ns" / s1acqe 1 "not answered (9)" 2 "schedule not obtained" 3 "schedule not applicable" 4 "item not applicable" 5 "5+ gcses at a-c" 6 "1-4 gcses at a-c" 7 "5+ gcses at d-g" 8 "1-4 gcses at d-g" 9 "none reported" . EXECUTE.


Here is the SPSS syntax that weights the data and then estimates the logit model.


WEIGHT BY weight.

LOGISTIC REGRESSION VARIABLES s15a_c /METHOD=ENTER girls chinese indian white bangldsh pakistan prof_man o_non_mn sklld_mn sm_sklld /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) CUT(.5).


These results are now the same as in the published model

spss

published


Complex Samples Logistic Regression.

As a final check I undertake the analysis in SPSS using the Comples Samples approach.

The code required for the complex sample analysis plans is

CSPLAN ANALYSIS
/PLAN FILE='C:\Users\Vernon\OneDrive - University of Edinburgh\Documents\ycs_9_2017\logit.csaplan'
/PLANVARS ANALYSISWEIGHT=weight
/SRSESTIMATOR TYPE=WOR
/PRINT PLAN
/DESIGN
/ESTIMATOR TYPE=WR.

The code required for the complex sample logistic regression model is

CSLOGISTIC s15a_c(LOW) WITH girls chinese indian white pakistan bangldsh prof_man o_non_mn
sklld_mn sm_sklld
/PLAN FILE='C:\Users\Vernon\OneDrive - University of '+
'Edinburgh\Documents\ycs_9_2017\logit.csaplan'
/MODEL girls chinese indian white bangldsh pakistan prof_man o_non_mn sklld_mn sm_sklld
/INTERCEPT INCLUDE=YES SHOW=YES
/STATISTICS PARAMETER SE
/TEST TYPE=F PADJUST=LSD
/MISSING CLASSMISSING=EXCLUDE
/CRITERIA MXITER=100 MXSTEP=5 PCONVERGE=[1e-006 RELATIVE] LCONVERGE=[0] CHKSEP=20 CILEVEL=95
/PRINT SUMMARY CLASSTABLE VARIABLEINFO SAMPLEINFO.

Here is a screen shot of the SPSS output.

spss_Slide

There results are the same as the results in R

It is worth noting that there are (at least) two ways of estimating a logit model in SPSS in the presence of survey weights.

The __Complex Samples__ approach returns the same results as __svy__ in _R_.

By contrast weighting the dataset first, and then estimating a standard logistic regression model leads to different standard errors.

Detective work was required to arrive at this conclusion.

This passage of work underlines the requirement to clearly state the software used (including versions, libraries and dependencies) and as much detail as possible relating to the technique used.


Duplicating the Connolly (2006) Model Results in Stata

In this section I duplicate the results produced in Connolly 2006 using Stata.

We have had to move outside of the workflow in Jupyter (to move to SPSS).

Just in case we should make certain that we have the correct dataset in the frame.

In [4]:
load ("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.rda")
ls()
Out[4]:
"mydata4.df"

I will now export data frame to Stata format using the foreign library.

In [7]:
library(foreign)
write.dta(mydata4.df, "C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.dta")

You MUST have Stata on your machine!

This section uses ipystata to run Stata via Jupyter magic see
http://dev-ii-seminar.readthedocs.io/en/latest/notebooks/Stata_in_jupyter.html .

You can install IPyStata 0.3.0 using the following syntax

pip install ipystata

at your command line prompt i.e. c:\Users\Vernon .

This facility is provided here

https://github.com/TiesdeKok/ipystata

The author is Ties de Kok
e-mail: t.c.j.dekok@tilburguniversity.edu
Twitter: @TiesdeKok

You MUST have Stata on your machine!


This cell below imports ipystata so that we can run Stata within this notebook.

You MUST have Stata on your machine!

You MUST CHANGE the Jupyter kernel to PYTHON

Use the Kernel menu above.

Python is native to Jupyter so you will have this kernel.

In [1]:
import ipystata

If you have an error that looks a bit like this

Error in parse(text = x, srcfile = src): 1:8: unexpected symbol
1: import ipystata

Then you may probably have changed kernel

You MUST CHANGE the Jupyter kernel to PYTHON using the drop down menu Kernel above.


We are now working in Python using Stata via magic cells!

In [2]:
%%stata -o mydata4.df
codebook, compact
Variable        Obs Unique      Mean     Min      Max  Label
------------------------------------------------------------
serial        12789  12789  212370.3  200001   231392  se...
weight        12789    178  .9822923  .60253  2.51757  we...
sex           12789      2  3.532411       3        4  sex
s1a_c         12789     14  5.526624       0       13  s1a_c
a58           12789      8  4.265619       4       11  a58
s1eth         12789      3  5.115255       5        7  s1eth
s1acqe        12789      5  5.651576       5        9  s1...
pseg          12789      1         0       0        0  pseg
prof_man      12789      2  .2561576       0        1  pr...
o_non_man     12789      2  .2298851       0        1  o_...
skilled_man   12789      2  .3528814       0        1  sk...
semi_skilled  12789      2  .1215107       0        1  se...
pseg5         12789      2  .0395653       0        1  pseg5
pseg6         12789      1         0       0        0  pseg6
pseg7         12789      1         0       0        0  pseg7
s15a_c        12789      2  .6023927       0        1  s1...
girls         12789      2  .5324107       0        1  girls
ethnic1       12789      6  1.151536       1        6  et...
white         12789      2  .9353351       0        1  white
black         12789      2  .0140746       0        1  black
indian        12789      2  .0288529       0        1  in...
pakistani     12789      2  .0124326       0        1  pa...
bangladeshi   12789      2   .004066       0        1  ba...
chinese       12789      2  .0052389       0        1  ch...
other         12789      1         0       0        0  other
------------------------------------------------------------
> ta", replace
In [6]:
%%stata -o mydata4.df
svyset [pweight=weight]
* you may need to set the line size to stop the table going wonky *
set linesize 100
svy:logit s15a_c girls chinese indian white pakistani bangladeshi prof_man o_non_man skilled_man semi_skilled
      pweight: weight
          VCE: linearized
  Single unit: missing
     Strata 1: <one>
         SU 1: <observations>
        FPC 1: <zero>
> emi_skilled
(running logit on estimation sample)

Survey: Logistic regression

Number of strata   =         1                  Number of obs      =     12789
Number of PSUs     =     12789                  Population size    = 12562.536
                                                Design df          =     12788
                                                F(  10,  12779)    =    113.58
                                                Prob > F           =    0.0000

------------------------------------------------------------------------------
             |             Linearized
      s15a_c |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       girls |   .4045638   .0392609    10.30   0.000     .3276067     .481521
     chinese |   2.002307   .3773355     5.31   0.000     1.262673    2.741941
      indian |   1.065842   .2082879     5.12   0.000      .657567    1.474118
       white |   .6431364   .1711832     3.76   0.000     .3075918     .978681
   pakistani |   .5313644   .2450316     2.17   0.030     .0510659    1.011663
 bangladeshi |   .7661585   .3448563     2.22   0.026     .0901887    1.442128
    prof_man |   2.192092   .1086303    20.18   0.000      1.97916    2.405023
   o_non_man |    1.77251   .1079307    16.42   0.000      1.56095     1.98407
 skilled_man |   .9321662   .1041115     8.95   0.000      .728092     1.13624
semi_skilled |   .5758727   .1126428     5.11   0.000      .355076    .7966693
       _cons |  -2.208288   .1980157   -11.15   0.000    -2.596429   -1.820148
------------------------------------------------------------------------------

Here are the result from R

Survey design: svydesign(id = ~serial, data = mydata4.df, weight = ~weight)

variable Estimate Std. Error t value Pr
(Intercept) -2.20829 0.19802 -11.152 < 2e-16
girls 0.40456 0.03926 10.305 < 2e-16
chinese 2.00231 0.37734 5.306 1.14e-07
indian 1.06584 0.20829 5.117 3.15e-07
white 0.64314 0.17118 3.757 0.000173
bangladeshi 0.76616 0.34486 2.222 0.026323
pakistani 0.53136 0.24503 2.169 0.030135
prof_man 2.19209 0.10863 20.179 < 2e-16
o_non_man 1.77251 0.10793 16.423 < 2e-16
skilled_man 0.93217 0.10411 8.954 < 2e-16
semi_skilled 0.57587 0.11264 5.112 3.23e-07


Both their coefficients and the standard errors are the same in __ _R_ __ and in __Stata__


You MUST CHANGE the Jupyter kernel to _R_

Use the Kernel menu above.

The R kernel is required as we are moving back to R .

In this section I plan to export the data frame "mydata4.df" which is in the file "ycs9sw1_v2" into an Excel format file ".xlsx".

This required the package 'xlsx' to be installed in R .

install.packages('xlsx')

When I first tried this there was an error because a more up to date version of Java is required.

In [1]:
# if the work recommences with this section then the following libraries might be required.
library(foreign)
library(survey)
library(car)
library(dplyr)
library(weights)
library(dummies)
Warning message:
: package 'survey' was built under R version 3.2.5Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Warning message:
: package 'survival' was built under R version 3.2.5
Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

Warning message:
: package 'car' was built under R version 3.2.5Warning message:
: package 'dplyr' was built under R version 3.2.5
Attaching package: 'dplyr'

The following object is masked from 'package:car':

    recode

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Warning message:
: package 'weights' was built under R version 3.2.5Loading required package: Hmisc
Warning message:
: package 'Hmisc' was built under R version 3.2.5Loading required package: lattice
Loading required package: Formula
Warning message:
: package 'Formula' was built under R version 3.2.5Loading required package: ggplot2
Warning message:
: package 'ggplot2' was built under R version 3.2.5
Error: package 'ggplot2' could not be loaded
Warning message:
: package 'dummies' was built under R version 3.2.5dummies-1.5.6 provided by Decision Patterns

Warning message:
: package 'xlsx' was built under R version 3.2.5Loading required package: rJava
Warning message:
: package 'rJava' was built under R version 3.2.5Loading required package: xlsxjars
Warning message:
: package 'xlsxjars' was built under R version 3.2.5
In [ ]:
# this library is required.
library(xlsx)
In [2]:
load ("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.rda")
ls()
Out[2]:
"mydata4.df"
In [3]:
write.xlsx(mydata4.df, "C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.xlsx")

A file called "ycs9sw1_v2.xlsx" has now been written from within R.


Duplicating the Connolly (2006) Model Results in Python

In this section I will attempt to duplicate the logit model Table 5 p.20 Connolly (2006) in Python.

You MUST CHANGE the Jupyter kernel to PYTHON

Use the Kernel menu above.

Python is native to Jupyter so you will have this kernel.


First we have to "import" a package called "pandas".

Pandas is a software library written for the Python programming language for data manipulation and analysis.

In [1]:
import pandas as pd

If you have an error that looks a bit like this

Error in parse(text = x, srcfile = src): :1:8: unexpected symbol 1: import pandas

Then you may probably have changed kernel

You MUST CHANGE the Jupyter kernel to PYTHON using the drop down menu Kernel above

Using "read_excel" which is part of pandas which I have already loaded into "pd", I now construct the data frame "df" reading in the data from the Excel (xlsx) file.

In [2]:
df = pd.read_excel("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.xlsx")
df.head()
Out[2]:
serial weight sex s1a_c a58 s1eth s1acqe pseg prof_man o_non_man ... s15a_c girls ethnic1 white black indian pakistani bangladeshi chinese other
1 200001 0.87518 female 9 white white 5+ gcses at a*-c 0 1 0 ... 1 1 1 1 0 0 0 0 0 0
2 200004 0.97615 male 9 white white 5+ gcses at a*-c 0 0 1 ... 1 0 1 1 0 0 0 0 0 0
3 200005 0.97615 male 9 indian asian groups 5+ gcses at a*-c 0 0 0 ... 1 0 3 0 0 1 0 0 0 0
4 200006 0.97615 male 9 white white 5+ gcses at a*-c 0 0 1 ... 1 0 1 1 0 0 0 0 0 0
8 200014 0.95928 female 2 white white 1-4 gcses at a*-c 0 0 0 ... 0 1 1 1 0 0 0 0 0 0

5 rows × 25 columns

Python is more general purpose and not primarily orientated towards social science data analysis. Therefore some things are a little more fiddly.

For example before estimating the logistic regression models we must set a constant for all case (int=1).

In [3]:
df['Int']=1

Examining the data in the data frame "df".

In [20]:
df.head()
Out[20]:
serial weight sex s1a_c a58 s1eth s1acqe pseg prof_man o_non_man ... s15a_c girls ethnic1 white black indian pakistani bangladeshi chinese other
1 200001 0.87518 female 9 white white 5+ gcses at a*-c 0 1 0 ... 1 1 1 1 0 0 0 0 0 0
2 200004 0.97615 male 9 white white 5+ gcses at a*-c 0 0 1 ... 1 0 1 1 0 0 0 0 0 0
3 200005 0.97615 male 9 indian asian groups 5+ gcses at a*-c 0 0 0 ... 1 0 3 0 0 1 0 0 0 0
4 200006 0.97615 male 9 white white 5+ gcses at a*-c 0 0 1 ... 1 0 1 1 0 0 0 0 0 0
8 200014 0.95928 female 2 white white 1-4 gcses at a*-c 0 0 0 ... 0 1 1 1 0 0 0 0 0 0

5 rows × 25 columns

In [21]:
df.describe()
Out[21]:
serial weight s1a_c pseg prof_man o_non_man skilled_man semi_skilled pseg5 pseg6 ... s15a_c girls ethnic1 white black indian pakistani bangladeshi chinese other
count 12789.000000 12789.000000 12789.000000 12789 12789.000000 12789.000000 12789.000000 12789.000000 12789.000000 12789 ... 12789.000000 12789.000000 12789.000000 12789.000000 12789.000000 12789.000000 12789.000000 12789.000000 12789.000000 12789
mean 212370.330988 0.982292 5.526624 0 0.256158 0.229885 0.352881 0.121511 0.039565 0 ... 0.602393 0.532411 1.151536 0.935335 0.014075 0.028853 0.012433 0.004066 0.005239 0
std 7442.695401 0.350797 3.671873 0 0.436527 0.420775 0.477885 0.326733 0.194943 0 ... 0.489423 0.498968 0.643798 0.245943 0.117803 0.167400 0.110810 0.063638 0.072193 0
min 200001.000000 0.602530 0.000000 0 0.000000 0.000000 0.000000 0.000000 0.000000 0 ... 0.000000 0.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0
25% 206648.000000 0.762780 2.000000 0 0.000000 0.000000 0.000000 0.000000 0.000000 0 ... 0.000000 0.000000 1.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0
50% 211922.000000 0.875030 6.000000 0 0.000000 0.000000 0.000000 0.000000 0.000000 0 ... 1.000000 1.000000 1.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0
75% 217230.000000 1.030390 9.000000 0 1.000000 0.000000 1.000000 0.000000 0.000000 0 ... 1.000000 1.000000 1.000000 1.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0
max 231392.000000 2.517570 13.000000 0 1.000000 1.000000 1.000000 1.000000 1.000000 0 ... 1.000000 1.000000 6.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 0

8 rows × 21 columns

In [3]:
import statsmodels.api as sm
In [6]:
list(df)
Out[6]:
['serial',
 'weight',
 'sex',
 's1a_c',
 'a58',
 's1eth',
 's1acqe',
 'pseg',
 'prof_man',
 'o_non_man',
 'skilled_man',
 'semi_skilled',
 'pseg5',
 'pseg6',
 'pseg7',
 's15a_c',
 'girls',
 'ethnic1',
 'white',
 'black',
 'indian',
 'pakistani',
 'bangladeshi',
 'chinese',
 'other',
 'Int']
In [7]:
independentVar = ['girls', 'chinese', 'indian', 'white', 'bangladeshi', 'pakistani', 'prof_man','o_non_man','skilled_man','semi_skilled', 'Int']
logReg = sm.Logit(df['s15a_c'] , df[independentVar]) 
answer = logReg.fit()
Optimization terminated successfully.
         Current function value: 0.625258
         Iterations 5
In [8]:
answer.summary()
Out[8]:
Logit Regression Results
Dep. Variable: s15a_c No. Observations: 12789
Model: Logit Df Residuals: 12778
Method: MLE Df Model: 10
Date: Thu, 22 Jun 2017 Pseudo R-squ.: 0.06960
Time: 16:57:45 Log-Likelihood: -7996.4
converged: True LL-Null: -8594.6
LLR p-value: 8.895e-251
coef std err z P>|z| [95.0% Conf. Int.]
girls 0.3239 0.038 8.519 0.000 0.249 0.398
chinese 1.8696 0.347 5.393 0.000 1.190 2.549
indian 1.0400 0.195 5.331 0.000 0.658 1.422
white 0.6486 0.158 4.095 0.000 0.338 0.959
bangladeshi 0.7172 0.330 2.173 0.030 0.070 1.364
pakistani 0.4700 0.228 2.059 0.040 0.023 0.917
prof_man 2.0805 0.106 19.629 0.000 1.873 2.288
o_non_man 1.6869 0.105 16.007 0.000 1.480 1.893
skilled_man 0.8715 0.102 8.564 0.000 0.672 1.071
semi_skilled 0.5475 0.110 4.972 0.000 0.332 0.763
Int -1.6659 0.186 -8.962 0.000 -2.030 -1.302
In [8]:
from patsy import dmatrices
In [9]:
y, x = dmatrices('s15a_c ~ 1 + girls + chinese + indian + white + bangladeshi + pakistani + prof_man + o_non_man + skilled_man + semi_skilled' , df)
In [10]:
sm.GLM(endog=y, exog=x, family=sm.families.Binomial(), data_weights=df['weight']).fit().summary()
Out[10]:
Generalized Linear Model Regression Results
Dep. Variable: s15a_c No. Observations: 12789
Model: GLM Df Residuals: 12778
Model Family: Binomial Df Model: 10
Link Function: logit Scale: 1.0
Method: IRLS Log-Likelihood: -7996.4
Date: Mon, 26 Jun 2017 Deviance: 15993.
Time: 12:50:00 Pearson chi2: 1.28e+04
No. Iterations: 6
coef std err z P>|z| [95.0% Conf. Int.]
Intercept -1.6659 0.186 -8.962 0.000 -2.030 -1.302
girls 0.3239 0.038 8.519 0.000 0.249 0.398
chinese 1.8696 0.347 5.393 0.000 1.190 2.549
indian 1.0400 0.195 5.331 0.000 0.658 1.422
white 0.6486 0.158 4.095 0.000 0.338 0.959
bangladeshi 0.7172 0.330 2.173 0.030 0.070 1.364
pakistani 0.4700 0.228 2.059 0.040 0.023 0.917
prof_man 2.0805 0.106 19.629 0.000 1.873 2.288
o_non_man 1.6869 0.105 16.007 0.000 1.480 1.893
skilled_man 0.8715 0.102 8.564 0.000 0.672 1.071
semi_skilled 0.5475 0.110 4.972 0.000 0.332 0.763

Beware!

These results do not appear to have been weighted.


In [14]:
# Here is another attempt...

logmodel=sm.GLM(endog=y, exog=x, family=sm.families.Binomial(sm.families.links.logit)).fit()
#sm.GLM(, family=sm.families.Binomial(), data_weights=df['weight']).fit().summary()
logmodel.summary()
Out[14]:
Generalized Linear Model Regression Results
Dep. Variable: s15a_c No. Observations: 12789
Model: GLM Df Residuals: 12778
Model Family: Binomial Df Model: 10
Link Function: logit Scale: 1.0
Method: IRLS Log-Likelihood: -7996.4
Date: Mon, 26 Jun 2017 Deviance: 15993.
Time: 12:54:07 Pearson chi2: 1.28e+04
No. Iterations: 6
coef std err z P>|z| [95.0% Conf. Int.]
Intercept -1.6659 0.186 -8.962 0.000 -2.030 -1.302
girls 0.3239 0.038 8.519 0.000 0.249 0.398
chinese 1.8696 0.347 5.393 0.000 1.190 2.549
indian 1.0400 0.195 5.331 0.000 0.658 1.422
white 0.6486 0.158 4.095 0.000 0.338 0.959
bangladeshi 0.7172 0.330 2.173 0.030 0.070 1.364
pakistani 0.4700 0.228 2.059 0.040 0.023 0.917
prof_man 2.0805 0.106 19.629 0.000 1.873 2.288
o_non_man 1.6869 0.105 16.007 0.000 1.480 1.893
skilled_man 0.8715 0.102 8.564 0.000 0.672 1.071
semi_skilled 0.5475 0.110 4.972 0.000 0.332 0.763

Beware!

These results do not appear to have been weighted.


In [17]:
#Here is a third attempt ...

weight =df['weight']
logmodel2=sm.GLM(endog=y, exog=x, sample_weight =weight, family=sm.families.Binomial(sm.families.links.logit)).fit()

#sm.GLM(, family=sm.families.Binomial(), data_weights=df['weight']).fit().summary()
logmodel2.summary()
Out[17]:
Generalized Linear Model Regression Results
Dep. Variable: s15a_c No. Observations: 12789
Model: GLM Df Residuals: 12778
Model Family: Binomial Df Model: 10
Link Function: logit Scale: 1.0
Method: IRLS Log-Likelihood: -7996.4
Date: Mon, 26 Jun 2017 Deviance: 15993.
Time: 13:00:21 Pearson chi2: 1.28e+04
No. Iterations: 6
coef std err z P>|z| [95.0% Conf. Int.]
Intercept -1.6659 0.186 -8.962 0.000 -2.030 -1.302
girls 0.3239 0.038 8.519 0.000 0.249 0.398
chinese 1.8696 0.347 5.393 0.000 1.190 2.549
indian 1.0400 0.195 5.331 0.000 0.658 1.422
white 0.6486 0.158 4.095 0.000 0.338 0.959
bangladeshi 0.7172 0.330 2.173 0.030 0.070 1.364
pakistani 0.4700 0.228 2.059 0.040 0.023 0.917
prof_man 2.0805 0.106 19.629 0.000 1.873 2.288
o_non_man 1.6869 0.105 16.007 0.000 1.480 1.893
skilled_man 0.8715 0.102 8.564 0.000 0.672 1.071
semi_skilled 0.5475 0.110 4.972 0.000 0.332 0.763

Beware!

These results do not appear to have been weighted.


In order to investigate this further I will return to R .

Change the kernel back to R .

In [1]:
library(foreign)
library(survey)
library(car)
library(dplyr)
library(weights)
library(dummies)
library(xlsx)
Warning message:
: package 'survey' was built under R version 3.2.5Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Warning message:
: package 'survival' was built under R version 3.2.5
Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

Warning message:
: package 'car' was built under R version 3.2.5Warning message:
: package 'dplyr' was built under R version 3.2.5
Attaching package: 'dplyr'

The following object is masked from 'package:car':

    recode

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Warning message:
: package 'weights' was built under R version 3.2.5Loading required package: Hmisc
Warning message:
: package 'Hmisc' was built under R version 3.2.5Loading required package: lattice
Loading required package: Formula
Warning message:
: package 'Formula' was built under R version 3.2.5Loading required package: ggplot2
Warning message:
: package 'ggplot2' was built under R version 3.2.5
Error: package 'ggplot2' could not be loaded
Warning message:
: package 'dummies' was built under R version 3.2.5dummies-1.5.6 provided by Decision Patterns

Warning message:
: package 'xlsx' was built under R version 3.2.5Loading required package: rJava
Warning message:
: package 'rJava' was built under R version 3.2.5Loading required package: xlsxjars
Warning message:
: package 'xlsxjars' was built under R version 3.2.5
In [1]:
load("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.rda")
ls()
Out[1]:
"mydata4.df"
In [2]:
summary(mydata4.df)
Out[2]:
     serial           weight                        sex           s1a_c       
 Min.   :200001   Min.   :0.6025   not answered (9)   :   0   Min.   : 0.000  
 1st Qu.:206648   1st Qu.:0.7628   item not applicable:   0   1st Qu.: 2.000  
 Median :211922   Median :0.8750   male               :5980   Median : 6.000  
 Mean   :212370   Mean   :0.9823   female             :6809   Mean   : 5.527  
 3rd Qu.:217230   3rd Qu.:1.0304                              3rd Qu.: 9.000  
 Max.   :231392   Max.   :2.5176                              Max.   :13.000  
                                                                              
          a58                            s1eth                     s1acqe    
 white      :11962   white                  :11962   5+ gcses at a*-c :7747  
 indian     :  369   asian groups           :  647   1-4 gcses at a*-c:3071  
 pakistani  :  159   black groups           :  180   5+ gcses at d-g  :1190  
 carib.     :   73   not answered (9)       :    0   none reported    : 539  
 chin!ese   :   67   schedule not obtained  :    0   1-4 gcses at d-g : 242  
 other black:   58   schedule not applicable:    0   not answered (9) :   0  
 (Other)    :  101   (Other)                :    0   (Other)          :   0  
      pseg      prof_man        o_non_man       skilled_man    
 Min.   :0   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
 Median :0   Median :0.0000   Median :0.0000   Median :0.0000  
 Mean   :0   Mean   :0.2562   Mean   :0.2299   Mean   :0.3529  
 3rd Qu.:0   3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:1.0000  
 Max.   :0   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
                                                               
  semi_skilled        pseg5             pseg6       pseg7       s15a_c      
 Min.   :0.0000   Min.   :0.00000   Min.   :0   Min.   :0   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:0   1st Qu.:0   1st Qu.:0.0000  
 Median :0.0000   Median :0.00000   Median :0   Median :0   Median :1.0000  
 Mean   :0.1215   Mean   :0.03957   Mean   :0   Mean   :0   Mean   :0.6024  
 3rd Qu.:0.0000   3rd Qu.:0.00000   3rd Qu.:0   3rd Qu.:0   3rd Qu.:1.0000  
 Max.   :1.0000   Max.   :1.00000   Max.   :0   Max.   :0   Max.   :1.0000  
                                                                            
     girls           ethnic1          white            black        
 Min.   :0.0000   Min.   :1.000   Min.   :0.0000   Min.   :0.00000  
 1st Qu.:0.0000   1st Qu.:1.000   1st Qu.:1.0000   1st Qu.:0.00000  
 Median :1.0000   Median :1.000   Median :1.0000   Median :0.00000  
 Mean   :0.5324   Mean   :1.152   Mean   :0.9353   Mean   :0.01407  
 3rd Qu.:1.0000   3rd Qu.:1.000   3rd Qu.:1.0000   3rd Qu.:0.00000  
 Max.   :1.0000   Max.   :6.000   Max.   :1.0000   Max.   :1.00000  
                                                                    
     indian          pakistani        bangladeshi          chinese        
 Min.   :0.00000   Min.   :0.00000   Min.   :0.000000   Min.   :0.000000  
 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.000000  
 Median :0.00000   Median :0.00000   Median :0.000000   Median :0.000000  
 Mean   :0.02885   Mean   :0.01243   Mean   :0.004066   Mean   :0.005239  
 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.000000  
 Max.   :1.00000   Max.   :1.00000   Max.   :1.000000   Max.   :1.000000  
                                                                          
     other  
 Min.   :0  
 1st Qu.:0  
 Median :0  
 Mean   :0  
 3rd Qu.:0  
 Max.   :0  
            

In order to check the results produced using Python I will re-estimate the model in R but this time ignoring the sample weights.

In [3]:
modelnw<-glm (s15a_c ~ girls + chinese + indian +
                 white + bangladeshi + pakistani + 
                 pakistani + prof_man + o_non_man + 
                 skilled_man + semi_skilled, data = mydata4.df, family = "binomial")
In [4]:
summary(modelnw)
Out[4]:
Call:
glm(formula = s15a_c ~ girls + chinese + indian + white + bangladeshi + 
    pakistani + pakistani + prof_man + o_non_man + skilled_man + 
    semi_skilled, family = "binomial", data = mydata4.df)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.1823  -1.1162   0.6678   0.9093   1.7744  

Coefficients:
             Estimate Std. Error z value Pr(>|z|)    
(Intercept)  -1.66590    0.18588  -8.962  < 2e-16 ***
girls         0.32387    0.03802   8.519  < 2e-16 ***
chinese       1.86961    0.34667   5.393 6.93e-08 ***
indian        1.04002    0.19507   5.331 9.75e-08 ***
white         0.64860    0.15840   4.095 4.23e-05 ***
bangladeshi   0.71721    0.33011   2.173   0.0298 *  
pakistani     0.46998    0.22830   2.059   0.0395 *  
prof_man      2.08045    0.10599  19.629  < 2e-16 ***
o_non_man     1.68694    0.10539  16.007  < 2e-16 ***
skilled_man   0.87151    0.10177   8.564  < 2e-16 ***
semi_skilled  0.54747    0.11011   4.972 6.62e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 17189  on 12788  degrees of freedom
Residual deviance: 15993  on 12778  degrees of freedom
AIC: 16015

Number of Fisher Scoring iterations: 4

These un-weighted results are the same as the Python results. The weighting in not working in in Python.

Further investigation of how to incorporate survey weights into a logistic regression model using Python is required.


Replicating the Connolly (2006) Model Results with Quasi-Variance

In this section, following the duplication of the logistic rgression results in Table 3 (p.20) of Connolley (2006) I now undertake a replication activity.

In brief, I have concerns about the parameterisation of the ethnicity measure in the logistic regression model.

The reference category is 'Black' pupils.

This is a small category (n=180).

My suspicion is that this is a sub-optimal reference category.

I will investigate the relationship between the categories of ethnicity by estimating quasi-variance based comparison intervals.

An extensive and reproducible introduction is provided by Gayle and Lambert (2007).

The use of quasi-variance based comparison intervals allows a more subtle investigation of the differences between ethnic groups.

The procedure that will be used is described in Firth and De Menezes (2004) an implemented in the R library 'qvcalc'.

To run this procedure you must have __qvcalc__ installed in _R_.

code required in R
install.packages('qvcalc')


Warning.

Within this Jupyter notebook there has been a lot of non-routine work. For example I have 'swivel-chaired' between data analytical software packages and changed kernels.

It may from time to time be necessary to re-start the notebook depending on how stable your computing environment is.

In this section I re-start a R session.

In [1]:
library(foreign)
library(survey)
library(car)
library(dplyr)
library(weights)
library(dummies)

library(MASS)
library(qvcalc)
Warning message:
: package 'survey' was built under R version 3.2.5Loading required package: grid
Loading required package: Matrix
Loading required package: survival
Warning message:
: package 'survival' was built under R version 3.2.5
Attaching package: 'survey'

The following object is masked from 'package:graphics':

    dotchart

Warning message:
: package 'car' was built under R version 3.2.5Warning message:
: package 'dplyr' was built under R version 3.2.5
Attaching package: 'dplyr'

The following object is masked from 'package:car':

    recode

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Warning message:
: package 'weights' was built under R version 3.2.5Loading required package: Hmisc
Warning message:
: package 'Hmisc' was built under R version 3.2.5Loading required package: lattice
Loading required package: Formula
Warning message:
: package 'Formula' was built under R version 3.2.5Loading required package: ggplot2
Warning message:
: package 'ggplot2' was built under R version 3.2.5
Error: package 'ggplot2' could not be loaded
Warning message:
: package 'dummies' was built under R version 3.2.5dummies-1.5.6 provided by Decision Patterns


Attaching package: 'MASS'

The following object is masked from 'package:dplyr':

    select

Warning message:
: package 'qvcalc' was built under R version 3.2.5

Various WARNINGS will appear. Don't panic.

I re-load the R file "ycs9sw1_v2.rda".

In [2]:
load("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v2.rda")
ls()
Out[2]:
"mydata4.df"

The data frame is "mydata4.df".

Please double check that an earlier version has not bee loaded!

In [3]:
summary(mydata4.df)
Out[3]:
     serial           weight                        sex           s1a_c       
 Min.   :200001   Min.   :0.6025   not answered (9)   :   0   Min.   : 0.000  
 1st Qu.:206648   1st Qu.:0.7628   item not applicable:   0   1st Qu.: 2.000  
 Median :211922   Median :0.8750   male               :5980   Median : 6.000  
 Mean   :212370   Mean   :0.9823   female             :6809   Mean   : 5.527  
 3rd Qu.:217230   3rd Qu.:1.0304                              3rd Qu.: 9.000  
 Max.   :231392   Max.   :2.5176                              Max.   :13.000  
                                                                              
          a58                            s1eth                     s1acqe    
 white      :11962   white                  :11962   5+ gcses at a*-c :7747  
 indian     :  369   asian groups           :  647   1-4 gcses at a*-c:3071  
 pakistani  :  159   black groups           :  180   5+ gcses at d-g  :1190  
 carib.     :   73   not answered (9)       :    0   none reported    : 539  
 chin!ese   :   67   schedule not obtained  :    0   1-4 gcses at d-g : 242  
 other black:   58   schedule not applicable:    0   not answered (9) :   0  
 (Other)    :  101   (Other)                :    0   (Other)          :   0  
      pseg      prof_man        o_non_man       skilled_man    
 Min.   :0   Min.   :0.0000   Min.   :0.0000   Min.   :0.0000  
 1st Qu.:0   1st Qu.:0.0000   1st Qu.:0.0000   1st Qu.:0.0000  
 Median :0   Median :0.0000   Median :0.0000   Median :0.0000  
 Mean   :0   Mean   :0.2562   Mean   :0.2299   Mean   :0.3529  
 3rd Qu.:0   3rd Qu.:1.0000   3rd Qu.:0.0000   3rd Qu.:1.0000  
 Max.   :0   Max.   :1.0000   Max.   :1.0000   Max.   :1.0000  
                                                               
  semi_skilled        pseg5             pseg6       pseg7       s15a_c      
 Min.   :0.0000   Min.   :0.00000   Min.   :0   Min.   :0   Min.   :0.0000  
 1st Qu.:0.0000   1st Qu.:0.00000   1st Qu.:0   1st Qu.:0   1st Qu.:0.0000  
 Median :0.0000   Median :0.00000   Median :0   Median :0   Median :1.0000  
 Mean   :0.1215   Mean   :0.03957   Mean   :0   Mean   :0   Mean   :0.6024  
 3rd Qu.:0.0000   3rd Qu.:0.00000   3rd Qu.:0   3rd Qu.:0   3rd Qu.:1.0000  
 Max.   :1.0000   Max.   :1.00000   Max.   :0   Max.   :0   Max.   :1.0000  
                                                                            
     girls           ethnic1          white            black        
 Min.   :0.0000   Min.   :1.000   Min.   :0.0000   Min.   :0.00000  
 1st Qu.:0.0000   1st Qu.:1.000   1st Qu.:1.0000   1st Qu.:0.00000  
 Median :1.0000   Median :1.000   Median :1.0000   Median :0.00000  
 Mean   :0.5324   Mean   :1.152   Mean   :0.9353   Mean   :0.01407  
 3rd Qu.:1.0000   3rd Qu.:1.000   3rd Qu.:1.0000   3rd Qu.:0.00000  
 Max.   :1.0000   Max.   :6.000   Max.   :1.0000   Max.   :1.00000  
                                                                    
     indian          pakistani        bangladeshi          chinese        
 Min.   :0.00000   Min.   :0.00000   Min.   :0.000000   Min.   :0.000000  
 1st Qu.:0.00000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.000000  
 Median :0.00000   Median :0.00000   Median :0.000000   Median :0.000000  
 Mean   :0.02885   Mean   :0.01243   Mean   :0.004066   Mean   :0.005239  
 3rd Qu.:0.00000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.000000  
 Max.   :1.00000   Max.   :1.00000   Max.   :1.000000   Max.   :1.000000  
                                                                          
     other  
 Min.   :0  
 1st Qu.:0  
 Median :0  
 Mean   :0  
 3rd Qu.:0  
 Max.   :0  
            

I now re-estimate the logit model that "duplicated" the results in Table 3 (p.20) Connolly (2016).

In [4]:
mydesign2 <- svydesign(id = ~serial,data = mydata4.df, weight = ~weight)
In [5]:
model2<-svyglm (s15a_c ~ girls + chinese + indian +
                 white + bangladeshi + pakistani + 
                 pakistani + prof_man + o_non_man + 
                 skilled_man + semi_skilled, design=mydesign2, data = mydata4.df, family = "binomial")
Warning message:
In eval(expr, envir, enclos): non-integer #successes in a binomial glm!
In [6]:
summary(model2)
Out[6]:
Call:
svyglm(formula = s15a_c ~ girls + chinese + indian + white + 
    bangladeshi + pakistani + pakistani + prof_man + o_non_man + 
    skilled_man + semi_skilled, design = mydesign2, data = mydata4.df, 
    family = "binomial")

Survey design:
svydesign(id = ~serial, data = mydata4.df, weight = ~weight)

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  -2.20829    0.19802 -11.152  < 2e-16 ***
girls         0.40456    0.03926  10.305  < 2e-16 ***
chinese       2.00231    0.37734   5.306 1.14e-07 ***
indian        1.06584    0.20829   5.117 3.15e-07 ***
white         0.64314    0.17118   3.757 0.000173 ***
bangladeshi   0.76616    0.34486   2.222 0.026323 *  
pakistani     0.53136    0.24503   2.169 0.030135 *  
prof_man      2.19209    0.10863  20.179  < 2e-16 ***
o_non_man     1.77251    0.10793  16.423  < 2e-16 ***
skilled_man   0.93217    0.10411   8.954  < 2e-16 ***
semi_skilled  0.57587    0.11264   5.112 3.23e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1.000269)

Number of Fisher Scoring iterations: 4

Here is a reminder of the variables that are in the data frame "mydata4.df".

In [7]:
str(mydata4.df)
'data.frame':	12789 obs. of  25 variables:
 $ serial      : int  200001 200004 200005 200006 200014 200023 200024 200025 200032 200035 ...
 $ weight      : num  0.875 0.976 0.976 0.976 0.959 ...
 $ sex         : Factor w/ 4 levels "not answered (9)",..: 4 3 3 3 4 3 4 3 4 4 ...
 $ s1a_c       : int  9 9 9 9 2 2 7 3 10 1 ...
 $ a58         : Factor w/ 15 levels "not answered (99)",..: 4 4 8 4 4 4 4 4 4 4 ...
 $ s1eth       : Factor w/ 9 levels "not answered (9)",..: 5 5 7 5 5 5 5 5 5 5 ...
 $ s1acqe      : Factor w/ 9 levels "not answered (9)",..: 5 5 5 5 6 6 5 6 5 6 ...
 $ pseg        : int  0 0 0 0 0 0 0 0 0 0 ...
 $ prof_man    : int  1 0 0 0 0 1 0 1 0 0 ...
 $ o_non_man   : int  0 1 0 1 0 0 0 0 1 0 ...
 $ skilled_man : int  0 0 1 0 1 0 1 0 0 1 ...
 $ semi_skilled: int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg5       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg6       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg7       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ s15a_c      : num  1 1 1 1 0 0 1 0 1 0 ...
 $ girls       : num  1 0 0 0 1 0 1 0 1 1 ...
 $ ethnic1     : num  1 1 3 1 1 1 1 1 1 1 ...
 $ white       : num  1 1 0 1 1 1 1 1 1 1 ...
 $ black       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ indian      : num  0 0 1 0 0 0 0 0 0 0 ...
 $ pakistani   : num  0 0 0 0 0 0 0 0 0 0 ...
 $ bangladeshi : num  0 0 0 0 0 0 0 0 0 0 ...
 $ chinese     : num  0 0 0 0 0 0 0 0 0 0 ...
 $ other       : num  0 0 0 0 0 0 0 0 0 0 ...

In order to use the QV procedure I have to estimate the model with a multiple-categorie measure of "ethnicity".

The variable "ethnicity1" has already been created.

I check that "ethnicity1" is a factor.

In [8]:
levels(mydata4.df$ethnic1)
Out[8]:
NULL

The variable "ethnic1" is not a factor so I am going to declare as a factor.

In [9]:
mydata4.df$ethnic1  <- factor(mydata4.df$ethnic1 )
In [10]:
levels(mydata4.df$ethnic1)
Out[10]:
  1. "1"
  2. "2"
  3. "3"
  4. "4"
  5. "5"
  6. "6"
In [11]:
is.factor(mydata4.df$ethnic1)
Out[11]:
TRUE

The variable "ethnic1" is now a factor.

Here I remind myself of the variables in the data frame "mydata4.df" and check again that "ethnic1" is a factor in the dataset.

In [13]:
str(mydata4.df)
'data.frame':	12789 obs. of  25 variables:
 $ serial      : int  200001 200004 200005 200006 200014 200023 200024 200025 200032 200035 ...
 $ weight      : num  0.875 0.976 0.976 0.976 0.959 ...
 $ sex         : Factor w/ 4 levels "not answered (9)",..: 4 3 3 3 4 3 4 3 4 4 ...
 $ s1a_c       : int  9 9 9 9 2 2 7 3 10 1 ...
 $ a58         : Factor w/ 15 levels "not answered (99)",..: 4 4 8 4 4 4 4 4 4 4 ...
 $ s1eth       : Factor w/ 9 levels "not answered (9)",..: 5 5 7 5 5 5 5 5 5 5 ...
 $ s1acqe      : Factor w/ 9 levels "not answered (9)",..: 5 5 5 5 6 6 5 6 5 6 ...
 $ pseg        : int  0 0 0 0 0 0 0 0 0 0 ...
 $ prof_man    : int  1 0 0 0 0 1 0 1 0 0 ...
 $ o_non_man   : int  0 1 0 1 0 0 0 0 1 0 ...
 $ skilled_man : int  0 0 1 0 1 0 1 0 0 1 ...
 $ semi_skilled: int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg5       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg6       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg7       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ s15a_c      : num  1 1 1 1 0 0 1 0 1 0 ...
 $ girls       : num  1 0 0 0 1 0 1 0 1 1 ...
 $ ethnic1     : Factor w/ 6 levels "1","2","3","4",..: 1 1 3 1 1 1 1 1 1 1 ...
 $ white       : num  1 1 0 1 1 1 1 1 1 1 ...
 $ black       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ indian      : num  0 0 1 0 0 0 0 0 0 0 ...
 $ pakistani   : num  0 0 0 0 0 0 0 0 0 0 ...
 $ bangladeshi : num  0 0 0 0 0 0 0 0 0 0 ...
 $ chinese     : num  0 0 0 0 0 0 0 0 0 0 ...
 $ other       : num  0 0 0 0 0 0 0 0 0 0 ...
In [14]:
ls()
Out[14]:
  1. "model2"
  2. "mydata4.df"
  3. "mydesign2"
In [15]:
model3<-svyglm (s15a_c ~ factor(ethnic1) + girls + prof_man + o_non_man + 
                 skilled_man + semi_skilled, design=mydesign2, data = mydata4.df, family = "binomial")
Warning message:
In eval(expr, envir, enclos): non-integer #successes in a binomial glm!
In [16]:
summary(model3)
Out[16]:
Call:
svyglm(formula = s15a_c ~ factor(ethnic1) + girls + prof_man + 
    o_non_man + skilled_man + semi_skilled, design = mydesign2, 
    data = mydata4.df, family = "binomial")

Survey design:
svydesign(id = ~serial, data = mydata4.df, weight = ~weight)

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)    
(Intercept)      -1.56515    0.10196 -15.351  < 2e-16 ***
factor(ethnic1)2 -0.64314    0.17118  -3.757 0.000173 ***
factor(ethnic1)3  0.42271    0.12187   3.469 0.000525 ***
factor(ethnic1)4 -0.11177    0.17735  -0.630 0.528544    
factor(ethnic1)5  0.12302    0.30052   0.409 0.682278    
factor(ethnic1)6  1.35917    0.33721   4.031 5.59e-05 ***
girls             0.40456    0.03926  10.305  < 2e-16 ***
prof_man          2.19209    0.10863  20.179  < 2e-16 ***
o_non_man         1.77251    0.10793  16.423  < 2e-16 ***
skilled_man       0.93217    0.10411   8.954  < 2e-16 ***
semi_skilled      0.57587    0.11264   5.112 3.23e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1.000269)

Number of Fisher Scoring iterations: 4

BEWARE

The variable "ethnic1" is coded to match the ethnicity measure in Table 1 (p.7) Connolly (2006). However, the order of the dummy variables included in the logistic regression model in Table 3 (p.20) Connelly (2006) do not match.

This could not have easily been foreseen.

In the spirit of showing all of the workflow I have preseved this snippet of data wrangling.


A re-coded version of "ethnic1" is required.

Here is the original variable.

In [18]:
table(mydata4.df$ethnic1)
Out[18]:
    1     2     3     4     5     6 
11962   180   369   159    52    67 

The new variable will be called "ethnic2".

The reference category should be 'black' pupils (i.e. carib; afro.; other black).

Categories should be

  1. Black
  2. Chinese
  3. Indian
  4. White
  5. Bangladeshi
  6. Pakistani
  7. Others (but this category has been omitted from the analysis)
In [19]:
# create the new field,

mydata4.df$ethnic2 <- 7

# everyone is placed into category 7.

# recode the new field with values from the old field.
mydata4.df$ethnic2[mydata4.df$a58=="white"] <-4
mydata4.df$ethnic2[mydata4.df$a58=="carib."] <-1
mydata4.df$ethnic2[mydata4.df$a58=="afro."] <-1
mydata4.df$ethnic2[mydata4.df$a58=="other black"] <-1
mydata4.df$ethnic2[mydata4.df$a58=="indian"] <-3
mydata4.df$ethnic2[mydata4.df$a58=="pakistani"] <-6
mydata4.df$ethnic2[mydata4.df$a58=="bangladeshi"] <-5
mydata4.df$ethnic2[mydata4.df$a58=="chin!ese"] <-2
mydata4.df$ethnic2[mydata4.df$a58=="other asian"] <-7
mydata4.df$ethnic2[mydata4.df$a58=="any other"] <-7
mydata4.df$ethnic2[mydata4.df$a58=="mixed ethnic origin"] <-7
mydata4.df$ethnic2[mydata4.df$a58=="ref!used"] <-7
In [21]:
table(mydata4.df$ethnic2)
Out[21]:
    1     2     3     4     5     6 
  180    67   369 11962    52   159 

Just to check the old variable "ethnic1" and the new variable "ethnic2".

In [22]:
mytable <- table (mydata4.df$ethnic1,mydata4.df$ethnic2)
mytable # print table
Out[22]:
   
        1     2     3     4     5     6
  1     0     0     0 11962     0     0
  2   180     0     0     0     0     0
  3     0     0   369     0     0     0
  4     0     0     0     0     0   159
  5     0     0     0     0    52     0
  6     0    67     0     0     0     0

I will now try to re-estimate the model but with the ethnicity variable "ethnic2".

The data have been altered so I re-set the survey design.

In [23]:
mydesign3 <- svydesign(id = ~serial,data = mydata4.df, weight = ~weight)
In [24]:
model4<-svyglm (s15a_c ~ factor(ethnic2) + girls + prof_man + o_non_man + 
                 skilled_man + semi_skilled, design=mydesign3, data = mydata4.df, family = "binomial")
Warning message:
In eval(expr, envir, enclos): non-integer #successes in a binomial glm!
In [25]:
summary(model4)
Out[25]:
Call:
svyglm(formula = s15a_c ~ factor(ethnic2) + girls + prof_man + 
    o_non_man + skilled_man + semi_skilled, design = mydesign3, 
    data = mydata4.df, family = "binomial")

Survey design:
svydesign(id = ~serial, data = mydata4.df, weight = ~weight)

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)    
(Intercept)      -2.20829    0.19802 -11.152  < 2e-16 ***
factor(ethnic2)2  2.00231    0.37734   5.306 1.14e-07 ***
factor(ethnic2)3  1.06584    0.20829   5.117 3.15e-07 ***
factor(ethnic2)4  0.64314    0.17118   3.757 0.000173 ***
factor(ethnic2)5  0.76616    0.34486   2.222 0.026323 *  
factor(ethnic2)6  0.53136    0.24503   2.169 0.030135 *  
girls             0.40456    0.03926  10.305  < 2e-16 ***
prof_man          2.19209    0.10863  20.179  < 2e-16 ***
o_non_man         1.77251    0.10793  16.423  < 2e-16 ***
skilled_man       0.93217    0.10411   8.954  < 2e-16 ***
semi_skilled      0.57587    0.11264   5.112 3.23e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1.000269)

Number of Fisher Scoring iterations: 4

Note!

The results now duplicate Table 5 (p.20) Connolley (2006).


I now past the modelling results to the quasi-variance estimation package.

In [26]:
model4.qvs <- qvcalc(model4, "factor(ethnic2)")

I now get a summary of these results.

This includes the
parameter estimate (i.e. beta) "estimate";
conventional standard error "SE";
quasi-variance based standard error "quasiSE";
quasi-varianve based variance "quasiVar".

In [27]:
summary(model4.qvs, digits = 4)
Model call:  svyglm(formula = s15a_c ~ factor(ethnic2) + girls + prof_man +      o_non_man + skilled_man + semi_skilled, design = mydesign3,      data = mydata4.df, family = "binomial") 
Factor name:  factor(ethnic2) 
      estimate     SE quasiSE  quasiVar
    1   0.0000 0.0000 0.17011 0.0289357
    2   2.0023 0.3773 0.33645 0.1131998
    3   1.0658 0.2083 0.12014 0.0144326
    4   0.6431 0.1712 0.02034 0.0004138
    5   0.7662 0.3449 0.29977 0.0898622
    6   0.5314 0.2450 0.17612 0.0310191
Worst relative errors in SEs of simple contrasts (%):  -0.1 0.1 
Worst relative errors over *all* contrasts (%):  -0.4 0.1 

I now plot the estimates for "ethnicity2" along with quasi-variance based 95% comparison intervals.

In [28]:
plot(model4.qvs)

The levels for factor(ethnic2)

1 Black; 2 Chinese; 3 Indian; 4 White; 5 Bangladeshi; 6 Pakistani.


Comments

My suspicion that the 'Black' pupils category is a sub-optimal reference category is confirmed.

This is a small category (n=180), and there is a large comparison interval around this estimate.

Also, whilst the other five ethnic categories are significantly different to zero (when Black pupils are set as the reference category) the differences between some categories are not significant. For a fuller discussion of using quasi-variance comparison intervals see Gayle and Lambert 2007.

I will now re-estimate the model with 'White' pupils as the referene category.

I will re-organise the ethnic categories as follows

'White'
'Chinese'

Then the three South Asian categories

'Indian'
'Banglasdeshi'
'Pakistani'

Then finally...

'Black'

(Others are absent from the model)


Re-ordering the ethnicity variable "ethnic2".

Creating a new ethnicity variable "ethnic3".

In [29]:
# create the new field,

mydata4.df$ethnic3 <- 7

# everyone is placed into category 7.

# recode the new field with values from the old field.
mydata4.df$ethnic3[mydata4.df$a58=="white"] <-1
mydata4.df$ethnic3[mydata4.df$a58=="carib."] <-6
mydata4.df$ethnic3[mydata4.df$a58=="afro."] <-6
mydata4.df$ethnic3[mydata4.df$a58=="other black"] <-6
mydata4.df$ethnic3[mydata4.df$a58=="indian"] <-3
mydata4.df$ethnic3[mydata4.df$a58=="pakistani"] <-5
mydata4.df$ethnic3[mydata4.df$a58=="bangladeshi"] <-4
mydata4.df$ethnic3[mydata4.df$a58=="chin!ese"] <-2
mydata4.df$ethnic3[mydata4.df$a58=="other asian"] <-7
mydata4.df$ethnic3[mydata4.df$a58=="any other"] <-7
mydata4.df$ethnic3[mydata4.df$a58=="mixed ethnic origin"] <-7
mydata4.df$ethnic3[mydata4.df$a58=="ref!used"] <-7
In [30]:
table(mydata4.df$ethnic3)
Out[30]:
    1     2     3     4     5     6 
11962    67   369    52   159   180 

Just to check the old variable "ethnic1" and the new variable "ethnic3".

In [31]:
mytable <- table (mydata4.df$ethnic1,mydata4.df$ethnic3)
mytable # print table
Out[31]:
   
        1     2     3     4     5     6
  1 11962     0     0     0     0     0
  2     0     0     0     0     0   180
  3     0     0   369     0     0     0
  4     0     0     0     0   159     0
  5     0     0     0    52     0     0
  6     0    67     0     0     0     0

This looks satisfactory.

I will now try to re-estimate the model but with the ethnicity variable "ethnic2".

The data have been altered so I re-set the survey design.

In [32]:
mydesign4 <- svydesign(id = ~serial,data = mydata4.df, weight = ~weight)
In [33]:
model5<-svyglm (s15a_c ~ factor(ethnic3) + girls + prof_man + o_non_man + 
                 skilled_man + semi_skilled, design=mydesign4, data = mydata4.df, family = "binomial")
Warning message:
In eval(expr, envir, enclos): non-integer #successes in a binomial glm!
In [34]:
summary(model5)
Out[34]:
Call:
svyglm(formula = s15a_c ~ factor(ethnic3) + girls + prof_man + 
    o_non_man + skilled_man + semi_skilled, design = mydesign4, 
    data = mydata4.df, family = "binomial")

Survey design:
svydesign(id = ~serial, data = mydata4.df, weight = ~weight)

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)    
(Intercept)      -1.56515    0.10196 -15.351  < 2e-16 ***
factor(ethnic3)2  1.35917    0.33721   4.031 5.59e-05 ***
factor(ethnic3)3  0.42271    0.12187   3.469 0.000525 ***
factor(ethnic3)4  0.12302    0.30052   0.409 0.682278    
factor(ethnic3)5 -0.11177    0.17735  -0.630 0.528544    
factor(ethnic3)6 -0.64314    0.17118  -3.757 0.000173 ***
girls             0.40456    0.03926  10.305  < 2e-16 ***
prof_man          2.19209    0.10863  20.179  < 2e-16 ***
o_non_man         1.77251    0.10793  16.423  < 2e-16 ***
skilled_man       0.93217    0.10411   8.954  < 2e-16 ***
semi_skilled      0.57587    0.11264   5.112 3.23e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1.000269)

Number of Fisher Scoring iterations: 4

Note!

The results no longer duplicate Table 5 (p.20) Connolley (2006) but the results build upon, and extend, the work so they are a replication.


I now pass the results to the quasi-variance procedure.

In [35]:
model5.qvs <- qvcalc(model5, "factor(ethnic3)")
In [36]:
summary(model5.qvs, digits = 4)
Model call:  svyglm(formula = s15a_c ~ factor(ethnic3) + girls + prof_man +      o_non_man + skilled_man + semi_skilled, design = mydesign4,      data = mydata4.df, family = "binomial") 
Factor name:  factor(ethnic3) 
      estimate     SE quasiSE  quasiVar
    1   0.0000 0.0000 0.02034 0.0004138
    2   1.3592 0.3372 0.33645 0.1131998
    3   0.4227 0.1219 0.12014 0.0144326
    4   0.1230 0.3005 0.29977 0.0898622
    5  -0.1118 0.1773 0.17612 0.0310191
    6  -0.6431 0.1712 0.17011 0.0289357
Worst relative errors in SEs of simple contrasts (%):  -0.1 0.1 
Worst relative errors over *all* contrasts (%):  -0.4 0.1 

I now plot the results for "ethnicity3" along with quasi-variance based 95% comparison intervals.

In [37]:
plot(model5.qvs)

The levels for factor(ethnic3)

  1. White
  2. Chinese
  3. Indian
  4. Banglasdeshi
  5. Pakistani
  6. Black

(Others are absent from the model)

Comments

The results have been duplicated and then built upon. These results are a replication.

The model is improved by using 'White' pupils as the reference category. This is a large category and there is a small comparison interval around the estimate.

The model also tells a more theoretically useful substantive story. The use of quasi-variance based comparison intervals allows a more subtle investigation of the differences between ethnic groups.

There are some ethnic differences in school GCSE outcomes (5+ GCSEs at grades A - C).

Compared with the majority of pupils who are white those who are Chinese have better outcomes.

Indian pupils perform better than white pupils.

Bangladeshi and Pakistani pupils do have significantly different outcomes to white pupils.

Black pupils have significantly poorer outcomes than their white counterparts.

It is notable that the three south Asian ethnic groups are not significantly different to each other.

This hopefully illustrates that this model is better parameterised that the original model presented in Table 5 (p.20) Connolly (2006).


The analyses above have required some more data wrangling. Therefore it is prudent to save a new copy of the data.

I will take a look at the objects that are knocking around.

In [39]:
ls()
Out[39]:
  1. "model2"
  2. "model3"
  3. "model4"
  4. "model4.qvs"
  5. "model5"
  6. "model5.qvs"
  7. "mydata4.df"
  8. "mydesign2"
  9. "mydesign3"
  10. "mydesign4"
  11. "mytable"

To avoid confusion later and to help to keep the workflow clear I will create a new data frame "mydata5.df".

In [40]:
mydata5.df<-mydata4.df
str(mydata5.df)
'data.frame':	12789 obs. of  27 variables:
 $ serial      : int  200001 200004 200005 200006 200014 200023 200024 200025 200032 200035 ...
 $ weight      : num  0.875 0.976 0.976 0.976 0.959 ...
 $ sex         : Factor w/ 4 levels "not answered (9)",..: 4 3 3 3 4 3 4 3 4 4 ...
 $ s1a_c       : int  9 9 9 9 2 2 7 3 10 1 ...
 $ a58         : Factor w/ 15 levels "not answered (99)",..: 4 4 8 4 4 4 4 4 4 4 ...
 $ s1eth       : Factor w/ 9 levels "not answered (9)",..: 5 5 7 5 5 5 5 5 5 5 ...
 $ s1acqe      : Factor w/ 9 levels "not answered (9)",..: 5 5 5 5 6 6 5 6 5 6 ...
 $ pseg        : int  0 0 0 0 0 0 0 0 0 0 ...
 $ prof_man    : int  1 0 0 0 0 1 0 1 0 0 ...
 $ o_non_man   : int  0 1 0 1 0 0 0 0 1 0 ...
 $ skilled_man : int  0 0 1 0 1 0 1 0 0 1 ...
 $ semi_skilled: int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg5       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg6       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg7       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ s15a_c      : num  1 1 1 1 0 0 1 0 1 0 ...
 $ girls       : num  1 0 0 0 1 0 1 0 1 1 ...
 $ ethnic1     : Factor w/ 6 levels "1","2","3","4",..: 1 1 3 1 1 1 1 1 1 1 ...
 $ white       : num  1 1 0 1 1 1 1 1 1 1 ...
 $ black       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ indian      : num  0 0 1 0 0 0 0 0 0 0 ...
 $ pakistani   : num  0 0 0 0 0 0 0 0 0 0 ...
 $ bangladeshi : num  0 0 0 0 0 0 0 0 0 0 ...
 $ chinese     : num  0 0 0 0 0 0 0 0 0 0 ...
 $ other       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ ethnic2     : num  4 4 3 4 4 4 4 4 4 4 ...
 $ ethnic3     : num  1 1 3 1 1 1 1 1 1 1 ...
In [41]:
save(mydata5.df,file="C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v3.rda")

Here I make a Stata copy of the file just in case I required it for swivel chair activities later in the workflow.

In [ ]:
write.dta(mydata5.df, "C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v3.dta")

Replicating the Connolly (2006) Model Results Adding an Improved Social Class Measure (UK National Socio-economic Classification - NS-SEC)

In this next stage of the analysis I will explore importing an additions social class measure.

The measure of social class that is employed in Table 5 (p.20) Connelly (2006) is unconventional in social stratification research.

The National Socio-economic Classification (NS-SEC) is a commonly used measure in stratification research and is the measure used in official statistics and government research in the United Kingdom.

In the next stage of the analysis I replicate the analysis of school GCSE attainment using YCS Cohort 9 through the incorporation of a parental NS-SEC measure that was derrived by Croxford et al (2007).


Youth Cohort Time Series for England, Wales and Scotland, 1984-2002 UK Data Archive Study 5765

https://discover.ukdataservice.ac.uk/catalogue/?sn=5765

The Education and Youth Transitions project (EYT) was funded by the ESRC from 2003 to 2006.
A key part of the project was to create comparable time-series datasets for England, Wales and Scotland from the Youth Cohort Study (YCS) and Scottish School Leavers Survey (SSLS).

Downloaded: UK Data Service https://www.ukdataservice.ac.uk/
Date: 23rd June 2017
Time: 00:17

Croxford, L., Iannelli, C., Shapira, M. (2007). Youth Cohort Time Series for England, Wales and Scotland, 1984-2002. [data collection]. National Centre for Social Research, Scottish Centre for Social Research, University of Edinburgh. Centre for Educational Sociology, [original data producer(s)]. UK Data Service. SN: 5765, http://doi.org/10.5255/UKDA-SN-5765-1


Warning.

Within this Jupyter notebook there has been a lot of non-routine work. For example I have 'swivel-chaired' between data analytical software packages and changed kernels.

It may from time to time be necessary to re-start the notebook depending on how stable your computing environment is.

In this section I re-start a R session.


In [11]:
library(foreign)
library(survey)
library(car)
library(dplyr)
library(weights)
library(dummies)

library(MASS)
library(qvcalc)
Warning message:
: package 'weights' was built under R version 3.2.5Loading required package: Hmisc
Warning message:
: package 'Hmisc' was built under R version 3.2.5Loading required package: ggplot2
Warning message:
: package 'ggplot2' was built under R version 3.2.5
Error: package 'ggplot2' could not be loaded

Various WARNINGS will appear. Don't panic.

From the Youth Cohort Time Series for England, Wales and Scotland, 1984-2002 UK Data Archive Study 5765, I will import a file called "ew_core". This is the core file containing pupils in England and Wales.

In [2]:
# This file is located on (my) OneDrive.

mydataew.df <- read.dta("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ew_core.dta")
In [3]:
summary(mydataew.df)
Out[3]:
    t0cohort        t0nation         t0caseid           t0source        
 Min.   :1984   england :107922   Min.   :   100001   Length:115179     
 1st Qu.:1988   wales   :  7257   1st Qu.:   131432   Class :character  
 Median :1993   scotland:     0   Median :228404103   Mode  :character  
 Mean   :1992                     Mean   :339926553                     
 3rd Qu.:1995                     3rd Qu.:680400520                     
 Max.   :1999                     Max.   :996602914                     
                                                                        
    t1weight         t2weight        t3weight                 t1resp      
 Min.   :0.1011   Min.   :-1.00   Min.   :-1.00   did not respond:     0  
 1st Qu.:0.7269   1st Qu.: 0.63   1st Qu.: 0.53   respondent     :115179  
 Median :0.9122   Median : 0.82   Median : 0.72                           
 Mean   :1.0000   Mean   : 0.92   Mean   : 0.83                           
 3rd Qu.:1.1777   3rd Qu.: 1.15   3rd Qu.: 1.07                           
 Max.   :3.8550   Max.   : 6.09   Max.   : 8.29                           
                  NA's   :63671   NA's   :42871                           
             t2resp                  t3resp         t0schtyp      
 no survey at t2:47618   did not respond:52334   Min.   :  1.000  
 did not respond:18042   respondent     :62845   1st Qu.:  2.000  
 respondent     :49519                           Median :  3.000  
                                                 Mean   :  3.195  
                                                 3rd Qu.:  3.000  
                                                 Max.   :999.000  
                                                                  
                 t0sex                     t0stay          t0sibs      
 not answered (9)   :    0   not answered     : 1481   Min.   :-9.000  
 item not applicable:    0   none             :    0   1st Qu.: 1.000  
 male               :54396   father and mother:93404   Median : 1.000  
 female             :60783   mother only      :14220   Mean   : 1.364  
                             father only      : 3022   3rd Qu.: 2.000  
                             other response   : 3052   Max.   :23.000  
                                                                       
           t0ethnic              t0house                t0dadpce    
 white         :101695   not answered: 2137   not answered  :10847  
 indian        :  2612   owned       :78293   yes           :16920  
 not answered  :  2046   rented      :18826   no            :34913  
 survey problem:  1989   other       : 1807   other response:14111  
 pakistani     :  1738   NA's        :14116   NA's          :38388  
 other response:  1715                                              
 (Other)       :  3384                                              
           t0mumpce               t0dadalv               t0mumalv    
 not answered  : 8624   not answered  :10847   not answered  : 8624  
 yes           :15815   yes           :16920   yes           :15815  
 no            :38718   no            :34913   no            :38718  
 other response:13634   other response:14111   other response:13634  
 NA's          :38388   NA's          :38388   NA's          :38388  
                                                                     
                                                                     
           t0daddeg               t0mumdeg                    t0dadjob    
 not answered  :13278   not answered  :11654   not answered (9)   : 9867  
 yes           :12862   yes           : 8826   item not applicable:    0  
 no            :39142   no            :44957   yes                :89865  
 other response:11509   other response:11354   no                 :15447  
 NA's          :38388   NA's          :38388                              
                                                                          
                                                                          
                t0mumjob                           t0truant    
 not answered (9)   : 6003   not answered              : 1539  
 item not applicable:    0   weeks at a time           : 2025  
 yes                :55195   days at a time            : 2473  
 no                 :53981   occasional days or lessons:43961  
                             never                     :65181  
                                                               
                                                               
                 t1att1                      t1att2     
 not answered (9)   : 3241   not answered (9)   : 3588  
 item not applicable:    0   item not applicable:    0  
 agree              :62450   agree              :40737  
 disagree           :33589   disagree           :54955  
 NA's               :15899   NA's               :15899  
                                                        
                                                        
                 t1att3                  t0region        t0dadsoc    
 not answered (9)   : 3658   other south east:24608   Min.   : -9.0  
 item not applicable:    0   north west      :14674   1st Qu.:126.0  
 agree              :61018   west midlands   :12439   Median :331.0  
 disagree           :34604   yorks & humber  :11942   Mean   :375.5  
 NA's               :15899   greater london  :11528   3rd Qu.:570.0  
                             (Other)         :39986   Max.   :999.0  
                             NA's            :    2   NA's   :30324  
    t0mumsoc        t0examst         t0examac         t0examaf     
 Min.   : -9.0   Min.   :-9.000   Min.   :-9.000   Min.   :-9.000  
 1st Qu.: -9.0   1st Qu.: 7.000   1st Qu.: 1.000   1st Qu.: 6.000  
 Median :390.0   Median : 8.000   Median : 4.000   Median : 8.000  
 Mean   :374.3   Mean   : 7.906   Mean   : 4.256   Mean   : 6.918  
 3rd Qu.:644.0   3rd Qu.: 9.000   3rd Qu.: 8.000   3rd Qu.: 9.000  
 Max.   :999.0   Max.   :18.000   Max.   :16.000   Max.   :16.000  
 NA's   :30324                                                     
    t0score          t0vocsbj       t0vocpas       t0othsbj     
 Min.   : -9.00   Min.   :0.00   Min.   :0.00   Min.   :0.0000  
 1st Qu.: 21.00   1st Qu.:0.00   1st Qu.:0.00   1st Qu.:0.0000  
 Median : 36.00   Median :0.00   Median :0.00   Median :0.0000  
 Mean   : 34.77   Mean   :0.13   Mean   :0.12   Mean   :0.1138  
 3rd Qu.: 50.00   3rd Qu.:0.00   3rd Qu.:0.00   3rd Qu.:0.0000  
 Max.   :112.00   Max.   :8.00   Max.   :8.00   Max.   :8.0000  
                  NA's   :8064   NA's   :8064                   
    t0othpas          t1dooct          t1donow           t0age      
 Min.   :0.00000   Min.   :-9.000   Min.   :-9.000   Min.   :-9.00  
 1st Qu.:0.00000   1st Qu.: 1.000   1st Qu.: 1.000   1st Qu.:16.00  
 Median :0.00000   Median : 3.000   Median : 3.000   Median :16.25  
 Mean   :0.09774   Mean   : 3.049   Mean   : 3.176   Mean   :15.85  
 3rd Qu.:0.00000   3rd Qu.: 5.000   3rd Qu.: 5.000   3rd Qu.:16.50  
 Max.   :8.00000   Max.   :10.000   Max.   :10.000   Max.   :16.75  
                                                     NA's   :3      
                t0dadse                     t0mumse     
 not answered (9)   :14725   not answered (9)   :21914  
 item not applicable: 3889   item not applicable: 3889  
 yes                :23196   yes                : 8972  
 no                 :73369   no                 :80404  
                                                        
                                                        
                                                        
                    t0gor                           t0urban     
 south east            :24602   not urban (lt 90%)      :57844  
 north west            :16553   urban area not in top 10:26023  
 west midlands         :12439   greater london          :11528  
 yorkshire & humberside:11648   west midlands ua        : 5417  
 london                :11528   greater manchester      : 5051  
 (Other)               :38407   (Other)                 : 9314  
 NA's                  :    2   NA's                    :    2  
    t0mumsec        t0dadsec        t0parsec        t0dadsc4    
 Min.   : 1.10   Min.   : 1.10   Min.   : 1.10   Min.   :  1.0  
 1st Qu.: 3.00   1st Qu.: 2.00   1st Qu.: 2.00   1st Qu.:  1.0  
 Median : 6.00   Median : 4.00   Median : 3.00   Median :  2.0  
 Mean   :30.04   Mean   :22.26   Mean   :14.03   Mean   : 54.1  
 3rd Qu.:99.00   3rd Qu.: 7.00   3rd Qu.: 6.00   3rd Qu.:  3.0  
 Max.   :99.00   Max.   :99.00   Max.   :99.00   Max.   :999.0  
 NA's   :38388   NA's   :38388   NA's   :38388                  
    t0mumsc4         t0parsc4         t0monthb       t3alev     
 Min.   :  1.00   Min.   :  1.00   Min.   : 0.000   no  :84329  
 1st Qu.:  2.00   1st Qu.:  1.00   1st Qu.: 3.000   yes :22786  
 Median :  3.00   Median :  2.00   Median : 6.000   NA's: 8064  
 Mean   : 62.62   Mean   : 45.91   Mean   : 6.332               
 3rd Qu.: 99.00   3rd Qu.:  3.00   3rd Qu.: 9.000               
 Max.   :999.00   Max.   :999.00   Max.   :99.000               
                                   NA's   :2                    
    t3nqf_a         t3_ucas          t3uscore        t3lev3       t3twoa     
 Min.   :0.000   Min.   :  0.00   Min.   :   0.00   no  :83834   no  :87006  
 1st Qu.:0.000   1st Qu.:  0.00   1st Qu.:   0.00   yes :23281   yes :20109  
 Median :0.000   Median :  0.00   Median :   0.00   NA's: 8064   NA's: 8064  
 Mean   :0.765   Mean   : 53.03   Mean   :  57.91                            
 3rd Qu.:2.000   3rd Qu.:  0.00   3rd Qu.:  38.00                            
 Max.   :3.000   Max.   :990.00   Max.   :1008.00                            
 NA's   :8064    NA's   :8064     NA's   :8064                               
    t3nowed                                             t3nowhe     
 Min.   :-9.0    missing information                        : 1539  
 1st Qu.: 0.0    no, in he but in other non-advanced cources:44591  
 Median : 0.0    yes, in he                                 :16715  
 Mean   : 0.4    NA's                                       :52334  
 3rd Qu.: 1.0                                                       
 Max.   : 1.0                                                       
 NA's   :52334                                                      
                                             t3degree    
 missing information                             :    0  
 no, studying for a non-advanced qualification   :46080  
 yes, studying for a degree                      :15226  
 no, studying for another advanced non-university:    0  
 NA's                                            :53873  
                                                         
                                                         
                          t3dooct                               t3donow     
 full time education          :24817   full time education          :27674  
 government supported training: 2385   full time job                :23202  
 full time job                :22145    unemployed                  : 4244  
  unemployed                  : 3778   government supported training: 2229  
 something else               : 7070   part-time job                : 2206  
 NA's                         :54984   (Other)                      : 2956  
                                       NA's                         :52668  
                          t2dooct                               t2donow     
 full time education          :43886   full time education          :42880  
 government supported training: 6084   full time job                :12702  
 full time job                :11721   government supported training: 5549  
  unemployed                  : 1907    unemployed                  : 2354  
 something else               : 1481   part-time job                : 1097  
 NA's                         :50100   (Other)                      :  888  
                                       NA's                         :49709  

To see the summary of the data use the scroll bar to scroll down.

In [4]:
str(mydataew.df)
'data.frame':	115179 obs. of  66 variables:
 $ t0cohort: int  1984 1984 1984 1984 1984 1984 1984 1984 1984 1984 ...
 $ t0nation: Factor w/ 3 levels "england","wales",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ t0caseid: int  301402257 301402259 301402260 301402652 301402654 301402656 301402660 301402661 301402666 301402668 ...
 $ t0source: chr  "ycs1" "ycs1" "ycs1" "ycs1" ...
 $ t1weight: num  1.25 2.1 1.05 1.61 2.1 ...
 $ t2weight: num  -1 3.732 0.866 -1 -1 ...
 $ t3weight: num  -1 3.254 0.802 -1 -1 ...
 $ t1resp  : Factor w/ 2 levels "did not respond",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ t2resp  : Factor w/ 3 levels "no survey at t2",..: 2 3 3 2 2 2 3 3 2 2 ...
 $ t3resp  : Factor w/ 2 levels "did not respond",..: 1 2 2 1 1 1 1 1 1 1 ...
 $ t0schtyp: int  3 3 3 3 3 3 3 3 3 3 ...
 $ t0sex   : Factor w/ 4 levels "not answered (9)",..: 4 3 4 3 3 4 4 4 3 4 ...
 $ t0stay  : Factor w/ 6 levels "not answered",..: 6 3 3 6 4 3 3 6 3 6 ...
 $ t0sibs  : int  2 2 1 1 0 1 3 2 2 7 ...
 $ t0ethnic: Factor w/ 9 levels "not answered",..: 2 3 3 2 2 2 9 3 2 2 ...
 $ t0house : Factor w/ 4 levels "not answered",..: 1 2 2 1 3 3 2 2 3 3 ...
 $ t0dadpce: Factor w/ 4 levels "not answered",..: NA NA NA NA NA NA NA NA NA NA ...
 $ t0mumpce: Factor w/ 4 levels "not answered",..: NA NA NA NA NA NA NA NA NA NA ...
 $ t0dadalv: Factor w/ 4 levels "not answered",..: NA NA NA NA NA NA NA NA NA NA ...
 $ t0mumalv: Factor w/ 4 levels "not answered",..: NA NA NA NA NA NA NA NA NA NA ...
 $ t0daddeg: Factor w/ 4 levels "not answered",..: NA NA NA NA NA NA NA NA NA NA ...
 $ t0mumdeg: Factor w/ 4 levels "not answered",..: NA NA NA NA NA NA NA NA NA NA ...
 $ t0dadjob: Factor w/ 4 levels "not answered (9)",..: 3 3 3 1 1 3 3 3 3 3 ...
 $ t0mumjob: Factor w/ 4 levels "not answered (9)",..: 4 4 3 1 3 4 4 4 4 4 ...
 $ t0truant: Factor w/ 5 levels "not answered",..: 4 4 5 5 4 4 3 5 5 5 ...
 $ t1att1  : Factor w/ 4 levels "not answered (9)",..: 4 3 3 4 4 4 3 3 3 3 ...
 $ t1att2  : Factor w/ 4 levels "not answered (9)",..: 4 4 3 3 3 3 4 4 4 4 ...
 $ t1att3  : Factor w/ 4 levels "not answered (9)",..: 3 3 3 4 4 4 3 4 4 3 ...
 $ t0region: Factor w/ 14 levels "not answered (99)",..: 11 11 11 11 11 11 11 11 11 11 ...
 $ t0dadsoc: int  -9 -9 615 -9 -9 620 535 872 532 872 ...
 $ t0mumsoc: int  -9 -9 460 -9 941 722 553 -9 620 958 ...
 $ t0examst: int  6 6 8 0 7 7 6 7 8 7 ...
 $ t0examac: int  0 0 6 0 0 0 0 1 0 1 ...
 $ t0examaf: int  3 0 7 0 2 3 1 5 3 5 ...
 $ t0score : int  10 0 34 0 7 9 4 17 10 19 ...
 $ t0vocsbj: int  NA NA NA NA NA NA NA NA NA NA ...
 $ t0vocpas: int  NA NA NA NA NA NA NA NA NA NA ...
 $ t0othsbj: int  0 0 2 0 0 0 0 1 0 2 ...
 $ t0othpas: int  0 0 1 0 0 0 0 0 0 2 ...
 $ t1dooct : int  5 6 6 -9 6 6 6 5 5 5 ...
 $ t1donow : int  5 6 6 -9 6 6 6 5 5 6 ...
 $ t0age   : num  -9 15.8 16.5 -9 -9 ...
 $ t0dadse : Factor w/ 4 levels "not answered (9)",..: 1 1 4 1 1 4 4 4 4 4 ...
 $ t0mumse : Factor w/ 4 levels "not answered (9)",..: 1 1 4 1 4 4 4 1 4 4 ...
 $ t0gor   : Factor w/ 11 levels "north east","north west",..: 7 7 7 7 7 7 7 7 7 7 ...
 $ t0urban : Factor w/ 12 levels "not urban (lt 90%)",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ t0mumsec: num  NA NA NA NA NA NA NA NA NA NA ...
 $ t0dadsec: num  NA NA NA NA NA NA NA NA NA NA ...
 $ t0parsec: num  NA NA NA NA NA NA NA NA NA NA ...
 $ t0dadsc4: int  99 99 3 99 99 3 3 3 3 3 ...
 $ t0mumsc4: int  99 99 2 99 3 2 3 99 3 3 ...
 $ t0parsc4: int  99 99 2 99 3 2 3 3 3 3 ...
 $ t0monthb: int  0 8 12 0 0 0 2 4 0 0 ...
 $ t3alev  : Factor w/ 2 levels "no","yes": NA NA NA NA NA NA NA NA NA NA ...
 $ t3nqf_a : num  NA NA NA NA NA NA NA NA NA NA ...
 $ t3_ucas : int  NA NA NA NA NA NA NA NA NA NA ...
 $ t3uscore: int  NA NA NA NA NA NA NA NA NA NA ...
 $ t3lev3  : Factor w/ 2 levels "no","yes": NA NA NA NA NA NA NA NA NA NA ...
 $ t3twoa  : Factor w/ 2 levels "no","yes": NA NA NA NA NA NA NA NA NA NA ...
 $ t3nowed : int  NA 0 0 NA NA NA NA NA NA NA ...
 $ t3nowhe : Factor w/ 3 levels "missing information",..: NA 2 2 NA NA NA NA NA NA NA ...
 $ t3degree: Factor w/ 4 levels "missing information",..: NA 2 2 NA NA NA NA NA NA NA ...
 $ t3dooct : Factor w/ 5 levels "full time education",..: NA 3 3 NA NA NA NA NA NA NA ...
 $ t3donow : Factor w/ 7 levels "full time education",..: NA 3 3 NA NA NA NA NA NA NA ...
 $ t2dooct : Factor w/ 5 levels "full time education",..: NA 3 3 NA NA NA NA NA NA NA ...
 $ t2donow : Factor w/ 7 levels "full time education",..: NA 3 3 NA NA NA NA NA NA NA ...
 - attr(*, "datalabel")= chr ""
 - attr(*, "time.stamp")= chr ""
 - attr(*, "formats")= chr  "%8.0g" "%8.0g" "%12.0g" "%5s" ...
 - attr(*, "types")= int  252 251 253 5 255 255 255 251 251 251 ...
 - attr(*, "val.labels")= chr  "" "t0nation" "" "" ...
 - attr(*, "var.labels")= chr  "year completed compulsory schooling" "national system" "id for time series" "source of data" ...
 - attr(*, "version")= int 8
 - attr(*, "label.table")=List of 47
  ..$ t0nation: Named int  1 2 3
  .. ..- attr(*, "names")= chr  "england" "wales" "scotland"
  ..$ t1resp  : Named int  0 1
  .. ..- attr(*, "names")= chr  "did not respond" "respondent"
  ..$ t2resp  : Named int  -1 0 1
  .. ..- attr(*, "names")= chr  "no survey at t2" "did not respond" "respondent"
  ..$ t3resp  : Named int  0 1
  .. ..- attr(*, "names")= chr  "did not respond" "respondent"
  ..$ t0schtyp: Named int  1 2 3 4 5 6 7 8
  .. ..- attr(*, "names")= chr  "6th form college" "comp to 16" "comp to 18" "grammar" ...
  ..$ t0sex   : Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "male" "female"
  ..$ t0stay  : Named int  -9 0 1 2 3 4
  .. ..- attr(*, "names")= chr  "not answered" "none" "father and mother" "mother only" ...
  ..$ t0ethnic: Named int  -9 -1 1 4 5 6 7 9 10
  .. ..- attr(*, "names")= chr  "not answered" "survey problem" "white" "black" ...
  ..$ t0house : Named int  -9 1 2 3
  .. ..- attr(*, "names")= chr  "not answered" "owned" "rented" "other"
  ..$ t0dadpce: Named int  -9 1 2 3
  .. ..- attr(*, "names")= chr  "not answered" "yes" "no" "other response"
  ..$ t0mumpce: Named int  -9 1 2 3
  .. ..- attr(*, "names")= chr  "not answered" "yes" "no" "other response"
  ..$ t0dadalv: Named int  -9 1 2 3
  .. ..- attr(*, "names")= chr  "not answered" "yes" "no" "other response"
  ..$ t0mumalv: Named int  -9 1 2 3
  .. ..- attr(*, "names")= chr  "not answered" "yes" "no" "other response"
  ..$ t0daddeg: Named int  -9 1 2 3
  .. ..- attr(*, "names")= chr  "not answered" "yes" "no" "other response"
  ..$ t0mumdeg: Named int  -9 1 2 3
  .. ..- attr(*, "names")= chr  "not answered" "yes" "no" "other response"
  ..$ t0dadjob: Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "yes" "no"
  ..$ t0mumjob: Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "yes" "no"
  ..$ t0truant: Named int  -9 1 2 3 4
  .. ..- attr(*, "names")= chr  "not answered" "weeks at a time" "days at a time" "occasional days or lessons" ...
  ..$ t1att1  : Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "agree" "disagree"
  ..$ t1att2  : Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "agree" "disagree"
  ..$ t1att3  : Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "agree" "disagree"
  ..$ t0region: Named int  -9 -6 -2 -1 1 2 3 4 5 6 ...
  .. ..- attr(*, "names")= chr  "not answered (99)" "schedule not obtained" "schedule not applicable" "item not applicable" ...
  ..$ t0dadsoc: Named int  100 101 102 103 110 111 112 113 120 121 ...
  .. ..- attr(*, "names")= chr  "asst secty nat govt    " "company gen manager    " "local govt officers    " "heo\\sen prl nat gov    " ...
  ..$ t0mumsoc: Named int  100 101 102 103 110 111 112 113 120 121 ...
  .. ..- attr(*, "names")= chr  "asst secty nat govt    " "company gen manager    " "local govt officers    " "heo\\sen prl nat gov    " ...
  ..$ t1dooct : Named int  0 1 2 3 4 5 6 7 8 9 ...
  .. ..- attr(*, "names")= chr  "nk" "school" "6th form college" "fe college" ...
  ..$ t1donow : Named int  0 1 2 3 4 5 6 7 8 9 ...
  .. ..- attr(*, "names")= chr  "nk" "school" "6th form college" "fe college" ...
  ..$ t0dadse : Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "yes" "no"
  ..$ t0mumse : Named int  -9 -1 1 2
  .. ..- attr(*, "names")= chr  "not answered (9)" "item not applicable" "yes" "no"
  ..$ t0gor   : Named int  1 2 3 4 5 6 7 8 9 10 ...
  .. ..- attr(*, "names")= chr  "north east" "north west" "yorkshire & humberside" "east midlands" ...
  ..$ t0urban : Named int  0 1 2 3 4 5 6 7 8 9 ...
  .. ..- attr(*, "names")= chr  "not urban (lt 90%)" "greater london" "west midlands ua" "greater manchester" ...
  ..$ t0mumsec: Named int  1 1 2 3 4 5 6 7 99
  .. ..- attr(*, "names")= chr  "higher managerial" "professional" "lower managerial and professional" "intermediate" ...
  ..$ t0dadsec: Named int  1 1 2 3 4 5 6 7 99
  .. ..- attr(*, "names")= chr  "higher managerial" "professional" "lower managerial and professional" "intermediate" ...
  ..$ t0parsec: Named int  1 1 2 3 4 5 6 7 99
  .. ..- attr(*, "names")= chr  "higher managerial" "professional" "lower managerial and professional" "intermediate" ...
  ..$ t0dadsc4: Named int  1 2 3 99
  .. ..- attr(*, "names")= chr  "managerial & professional" "intermediate" "working" "unclassified"
  ..$ t0mumsc4: Named int  1 2 3 99
  .. ..- attr(*, "names")= chr  "managerial & professional" "intermediate" "working" "unclassified"
  ..$ t0parsc4: Named int  1 2 3 99
  .. ..- attr(*, "names")= chr  "managerial & professional" "intermediate" "working" "unclassified"
  ..$ t0monthb: Named int  1 2 3 4 5 6 7 8 9 10 ...
  .. ..- attr(*, "names")= chr  "january" "february" "march" "april" ...
  ..$ t3alev  : Named int  0 1
  .. ..- attr(*, "names")= chr  "no" "yes"
  ..$ t3lev3  : Named int  0 1
  .. ..- attr(*, "names")= chr  "no" "yes"
  ..$ t3twoa  : Named int  0 1
  .. ..- attr(*, "names")= chr  "no" "yes"
  ..$ t3nowed : Named int  0 1
  .. ..- attr(*, "names")= chr  "in other status" "in full-time education"
  ..$ t3nowhe : Named int  -9 0 1
  .. ..- attr(*, "names")= chr  "missing information" "no, in he but in other non-advanced cources" "yes, in he"
  ..$ t3degree: Named int  -9 0 1 2
  .. ..- attr(*, "names")= chr  "missing information" "no, studying for a non-advanced qualification" "yes, studying for a degree" "no, studying for another advanced non-university"
  ..$ t3dooct : Named int  1 5 6 8 10
  .. ..- attr(*, "names")= chr  "full time education" "government supported training" "full time job" " unemployed" ...
  ..$ t3donow : Named int  1 5 6 7 8 9 10
  .. ..- attr(*, "names")= chr  "full time education" "government supported training" "full time job" "part-time job" ...
  ..$ t2dooct : Named int  1 5 6 8 10
  .. ..- attr(*, "names")= chr  "full time education" "government supported training" "full time job" " unemployed" ...
  ..$ t2donow : Named int  1 5 6 7 8 9 10
  .. ..- attr(*, "names")= chr  "full time education" "government supported training" "full time job" "part-time job" ...

The variables that I require are

t0cohort - the YCS cohort (i.e. year).

t0nation - identifies if the pupil is from the England and Wales data (this is just a check the dataset should be England and Wales on hence "ew" in "ew_core.dta" .

t0caseid - this is an id variable. However, it is not unqiue across YCS cohorts so must be used in conjuction with a cohort identifier.

t0source - identifies the YCS cohort (e.g. YCS 9).

t1weight - this is the sweep 1 survey weight.

t1resp - identifies if the pupil responded in sweep 1 of the survey.

t0parsec - this is the parental NS-SEC measure (8 category) that is derrived by Croxford et al. (2007). This is the measure that I require for the current replication exercise.

In [5]:
table(mydataew.df$t0cohort)
table(mydataew.df$t0source)
table(mydataew.df$t0parsec)
Out[5]:
 1984  1986  1988  1990  1993  1995  1997  1999 
 8064 16208 14116 14511 18021 15899 14662 13698 
Out[5]:
 ycs1 ycs10  ycs3  ycs4  ycs5  ycs7  ycs8  ycs9 
 8064 13698 16208 14116 14511 18021 15899 14662 
Out[5]:
  1.1   1.2     2     3     4     5     6     7    99 
 4533  7807 17171 11518 11349  4055  7335  4398  8625 

Get a subset of the data with only the variables needed.

In [6]:
myvarsew <- c("t0cohort", "t0nation", "t0caseid", "t0source", "t1weight", "t1resp", "t0parsec")
mydataew.df <- mydataew.df[myvarsew]
In [7]:
summary(mydataew.df)
Out[7]:
    t0cohort        t0nation         t0caseid           t0source        
 Min.   :1984   england :107922   Min.   :   100001   Length:115179     
 1st Qu.:1988   wales   :  7257   1st Qu.:   131432   Class :character  
 Median :1993   scotland:     0   Median :228404103   Mode  :character  
 Mean   :1992                     Mean   :339926553                     
 3rd Qu.:1995                     3rd Qu.:680400520                     
 Max.   :1999                     Max.   :996602914                     
                                                                        
    t1weight                  t1resp          t0parsec    
 Min.   :0.1011   did not respond:     0   Min.   : 1.10  
 1st Qu.:0.7269   respondent     :115179   1st Qu.: 2.00  
 Median :0.9122                            Median : 3.00  
 Mean   :1.0000                            Mean   :14.03  
 3rd Qu.:1.1777                            3rd Qu.: 6.00  
 Max.   :3.8550                            Max.   :99.00  
                                           NA's   :38388  

Now I get a subset of the cases (i.e. pupils) that are in the YCS cohort 9.

In [8]:
mydataew2.df <- mydataew.df[ which(mydataew.df$t0source=="ycs9"),]
In [52]:
summary(mydataew2.df)
table(mydataew2.df$t0source)
Out[52]:
    t0cohort        t0nation        t0caseid        t0source        
 Min.   :1997   england :13762   Min.   :200001   Length:14662      
 1st Qu.:1997   wales   :  900   1st Qu.:206123   Class :character  
 Median :1997   scotland:    0   Median :211589   Mode  :character  
 Mean   :1997                    Mean   :212056                     
 3rd Qu.:1997                    3rd Qu.:217027                     
 Max.   :1997                    Max.   :231392                     
    t1weight                  t1resp         t0parsec    
 Min.   :0.6025   did not respond:    0   Min.   : 1.10  
 1st Qu.:0.7661   respondent     :14662   1st Qu.: 2.00  
 Median :0.8779                           Median : 3.00  
 Mean   :1.0000                           Mean   :12.99  
 3rd Qu.:1.0576                           3rd Qu.: 6.00  
 Max.   :2.5176                           Max.   :99.00  
Out[52]:
 ycs9 
14662 

I will now check which objects are knocking around.

In [9]:
ls()
Out[9]:
  1. "mydataew.df"
  2. "mydataew2.df"
  3. "myvarsew"

I will now (re-)load the last version of my YCS cohort 9 dataset "ycs9sw1_v3.rda".

In [10]:
load("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v3.rda")
ls()
Out[10]:
  1. "mydata5.df"
  2. "mydataew.df"
  3. "mydataew2.df"
  4. "myvarsew"
In [55]:
str(mydata5.df)
'data.frame':	12789 obs. of  27 variables:
 $ serial      : int  200001 200004 200005 200006 200014 200023 200024 200025 200032 200035 ...
 $ weight      : num  0.875 0.976 0.976 0.976 0.959 ...
 $ sex         : Factor w/ 4 levels "not answered (9)",..: 4 3 3 3 4 3 4 3 4 4 ...
 $ s1a_c       : int  9 9 9 9 2 2 7 3 10 1 ...
 $ a58         : Factor w/ 15 levels "not answered (99)",..: 4 4 8 4 4 4 4 4 4 4 ...
 $ s1eth       : Factor w/ 9 levels "not answered (9)",..: 5 5 7 5 5 5 5 5 5 5 ...
 $ s1acqe      : Factor w/ 9 levels "not answered (9)",..: 5 5 5 5 6 6 5 6 5 6 ...
 $ pseg        : int  0 0 0 0 0 0 0 0 0 0 ...
 $ prof_man    : int  1 0 0 0 0 1 0 1 0 0 ...
 $ o_non_man   : int  0 1 0 1 0 0 0 0 1 0 ...
 $ skilled_man : int  0 0 1 0 1 0 1 0 0 1 ...
 $ semi_skilled: int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg5       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg6       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg7       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ s15a_c      : num  1 1 1 1 0 0 1 0 1 0 ...
 $ girls       : num  1 0 0 0 1 0 1 0 1 1 ...
 $ ethnic1     : Factor w/ 6 levels "1","2","3","4",..: 1 1 3 1 1 1 1 1 1 1 ...
 $ white       : num  1 1 0 1 1 1 1 1 1 1 ...
 $ black       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ indian      : num  0 0 1 0 0 0 0 0 0 0 ...
 $ pakistani   : num  0 0 0 0 0 0 0 0 0 0 ...
 $ bangladeshi : num  0 0 0 0 0 0 0 0 0 0 ...
 $ chinese     : num  0 0 0 0 0 0 0 0 0 0 ...
 $ other       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ ethnic2     : num  4 4 3 4 4 4 4 4 4 4 ...
 $ ethnic3     : num  1 1 3 1 1 1 1 1 1 1 ...

This data frame should have "ethnic2" and "ethnic3" in it.
If they are absent then a older file has been used.

I am now going to wrangle the data a little.

The reshape library is required if it is not already loaded.

In [56]:
library(reshape)
Warning message:
: package 'reshape' was built under R version 3.2.5
Attaching package: 'reshape'

The following object is masked from 'package:dplyr':

    rename

The following object is masked from 'package:Matrix':

    expand

The 'id" variables in file "ew_core" (i.e. Croxford's time series files) is not the same as in YCS cohort 9 file "ycs9sw1".
Therefore I am going to change the variable "t0caseid" which is in "ew_core" to "serial" which is the name of the "id" variable in "ycs9sw1".

In [57]:
mydataew2.df <- rename(mydataew2.df, c(t0caseid="serial"))
str(mydataew2.df)
'data.frame':	14662 obs. of  7 variables:
 $ t0cohort: int  1997 1997 1997 1997 1997 1997 1997 1997 1997 1997 ...
 $ t0nation: Factor w/ 3 levels "england","wales",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ serial  : int  200001 200004 200005 200006 200008 200012 200013 200014 200019 200022 ...
 $ t0source: chr  "ycs9" "ycs9" "ycs9" "ycs9" ...
 $ t1weight: num  0.875 0.976 0.976 0.976 1.841 ...
 $ t1resp  : Factor w/ 2 levels "did not respond",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ t0parsec: num  1.1 4 4 2 99 99 99 4 99 99 ...

Now I combine the file "ycs9sw1_v3" which is in data frame mydata5.df with "ew_core" which is in data frame mydataew2.df.

In [59]:
mydata6.df <- merge(mydata5.df, mydataew2.df,by="serial")
In [60]:
str(mydata6.df)
'data.frame':	12789 obs. of  33 variables:
 $ serial      : int  200001 200004 200005 200006 200014 200023 200024 200025 200032 200035 ...
 $ weight      : num  0.875 0.976 0.976 0.976 0.959 ...
 $ sex         : Factor w/ 4 levels "not answered (9)",..: 4 3 3 3 4 3 4 3 4 4 ...
 $ s1a_c       : int  9 9 9 9 2 2 7 3 10 1 ...
 $ a58         : Factor w/ 15 levels "not answered (99)",..: 4 4 8 4 4 4 4 4 4 4 ...
 $ s1eth       : Factor w/ 9 levels "not answered (9)",..: 5 5 7 5 5 5 5 5 5 5 ...
 $ s1acqe      : Factor w/ 9 levels "not answered (9)",..: 5 5 5 5 6 6 5 6 5 6 ...
 $ pseg        : int  0 0 0 0 0 0 0 0 0 0 ...
 $ prof_man    : int  1 0 0 0 0 1 0 1 0 0 ...
 $ o_non_man   : int  0 1 0 1 0 0 0 0 1 0 ...
 $ skilled_man : int  0 0 1 0 1 0 1 0 0 1 ...
 $ semi_skilled: int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg5       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg6       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ pseg7       : int  0 0 0 0 0 0 0 0 0 0 ...
 $ s15a_c      : num  1 1 1 1 0 0 1 0 1 0 ...
 $ girls       : num  1 0 0 0 1 0 1 0 1 1 ...
 $ ethnic1     : Factor w/ 6 levels "1","2","3","4",..: 1 1 3 1 1 1 1 1 1 1 ...
 $ white       : num  1 1 0 1 1 1 1 1 1 1 ...
 $ black       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ indian      : num  0 0 1 0 0 0 0 0 0 0 ...
 $ pakistani   : num  0 0 0 0 0 0 0 0 0 0 ...
 $ bangladeshi : num  0 0 0 0 0 0 0 0 0 0 ...
 $ chinese     : num  0 0 0 0 0 0 0 0 0 0 ...
 $ other       : num  0 0 0 0 0 0 0 0 0 0 ...
 $ ethnic2     : num  4 4 3 4 4 4 4 4 4 4 ...
 $ ethnic3     : num  1 1 3 1 1 1 1 1 1 1 ...
 $ t0cohort    : int  1997 1997 1997 1997 1997 1997 1997 1997 1997 1997 ...
 $ t0nation    : Factor w/ 3 levels "england","wales",..: 1 1 1 1 1 1 1 1 1 1 ...
 $ t0source    : chr  "ycs9" "ycs9" "ycs9" "ycs9" ...
 $ t1weight    : num  0.875 0.976 0.976 0.976 0.959 ...
 $ t1resp      : Factor w/ 2 levels "did not respond",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ t0parsec    : num  1.1 4 4 2 4 1.2 5 1.1 3 4 ...

If this has worked then mydata6.df should contain "ethnic2", "ethnic3" and "t0parsec".

Here is the first glimpse at the parental NS-SEC variable "t0parsec".

In [61]:
mytablenssec <- table(mydata6.df$t0parsec, mydata6.df$s15a_c)
mytablenssec # print table
Out[61]:
     
         0    1
  1.1  163  620
  1.2  215 1151
  2    936 2373
  3    831 1408
  4   1073 1072
  5    433  311
  6    879  538
  7    554  231
  99     1    0
In [62]:
prop.table (mytablenssec, 1)
Out[62]:
     
              0         1
  1.1 0.2081737 0.7918263
  1.2 0.1573939 0.8426061
  2   0.2828649 0.7171351
  3   0.3711478 0.6288522
  4   0.5002331 0.4997669
  5   0.5819892 0.4180108
  6   0.6203246 0.3796754
  7   0.7057325 0.2942675
  99  1.0000000 0.0000000
In [63]:
save(mydata6.df,file="C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v4.rda")
In [28]:
load ("C:/Users/Vernon/OneDrive - University of Edinburgh/Documents/ycs_9_2017/ycs9sw1_v4.rda")
ls()
Out[28]:
  1. "model6"
  2. "mydata5.df"
  3. "mydata6.df"
  4. "mydataew.df"
  5. "mydataew2.df"
  6. "mydesign5"
  7. "mytablenssec"
  8. "myvarsew"

Takin a second look at NS-SEC the social class variable.

In [30]:
mytablenssec <- table(mydata6.df$t0parsec, mydata6.df$s15a_c)
mytablenssec # print table
Out[30]:
     
         0    1
  1.1  163  620
  1.2  215 1151
  2    936 2373
  3    831 1408
  4   1073 1072
  5    433  311
  6    879  538
  7    554  231
  99     1    0

There is a missing value coded as "99".

In [31]:
mydata6.df$t0parsec[mydata6.df$t0parsec=="99"] <-NA
In [32]:
mytablenssec <- table(mydata6.df$t0parsec, mydata6.df$s15a_c)
mytablenssec # print table
Out[32]:
     
         0    1
  1.1  163  620
  1.2  215 1151
  2    936 2373
  3    831 1408
  4   1073 1072
  5    433  311
  6    879  538
  7    554  231

I now check that "t0parsec1" is a factor.

In [33]:
levels(mydata6.df$t0parsec )
Out[33]:
NULL

The variable "t0parsec" is not a factor so I am going to declare as a factor.

In [34]:
mydata6.df$t0parsec  <- factor(mydata6.df$t0parsec )
In [35]:
levels(mydata6.df$t0parsec)
Out[35]:
  1. "1.1"
  2. "1.2"
  3. "2"
  4. "3"
  5. "4"
  6. "5"
  7. "6"
  8. "7"
In [36]:
is.factor(mydata6.df$t0parsec)
Out[36]:
TRUE

I now estimate a logit model of school GCSE outcomes (5+ GCSEs and grade A - C).

It will be a survey based model (svy).

Outcome variable "s15a_c".

Explanatory variables "girls", "ethnic3", "t0parsec".

In [38]:
mydesign5 <- svydesign(id = ~serial,data = mydata6.df, weight = ~weight)
In [39]:
model6<-svyglm (s15a_c ~ girls + factor(ethnic3) + factor(t0parsec), design=mydesign5, data = mydata5.df, family = "binomial")
Warning message:
In eval(expr, envir, enclos): non-integer #successes in a binomial glm!
In [40]:
summary(model6)
Out[40]:
Call:
svyglm(formula = s15a_c ~ girls + factor(ethnic3) + factor(t0parsec), 
    design = mydesign5, data = mydata5.df, family = "binomial")

Survey design:
svydesign(id = ~serial, data = mydata6.df, weight = ~weight)

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)          0.71584    0.09351   7.655 2.07e-14 ***
girls                0.43422    0.03999  10.858  < 2e-16 ***
factor(ethnic3)2     1.49065    0.33070   4.508 6.61e-06 ***
factor(ethnic3)3     0.59759    0.12250   4.878 1.08e-06 ***
factor(ethnic3)4     0.32020    0.30585   1.047  0.29514    
factor(ethnic3)5     0.20791    0.18583   1.119  0.26323    
factor(ethnic3)6    -0.71506    0.17527  -4.080 4.54e-05 ***
factor(t0parsec)1.2  0.37121    0.11991   3.096  0.00197 ** 
factor(t0parsec)2   -0.41717    0.10001  -4.171 3.05e-05 ***
factor(t0parsec)3   -0.84849    0.10216  -8.305  < 2e-16 ***
factor(t0parsec)4   -1.43745    0.10249 -14.025  < 2e-16 ***
factor(t0parsec)5   -1.74863    0.12005 -14.565  < 2e-16 ***
factor(t0parsec)6   -1.94399    0.10789 -18.019  < 2e-16 ***
factor(t0parsec)7   -2.36128    0.12206 -19.345  < 2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1.000279)

Number of Fisher Scoring iterations: 4

I now pass the results to the quasi-variance procedure.

In [41]:
model6.qvs <- qvcalc(model6, "factor(t0parsec)")
In [42]:
summary(model6.qvs, digits = 4)
Model call:  svyglm(formula = s15a_c ~ girls + factor(ethnic3) + factor(t0parsec),      design = mydesign5, data = mydata5.df, family = "binomial") 
Factor name:  factor(t0parsec) 
        estimate     SE quasiSE quasiVar
    1.1   0.0000 0.0000 0.09167 0.008403
    1.2   0.3712 0.1199 0.07754 0.006012
    2    -0.4172 0.1000 0.04040 0.001632
    3    -0.8485 0.1022 0.04527 0.002049
    4    -1.4374 0.1025 0.04555 0.002075
    5    -1.7486 0.1201 0.07746 0.006000
    6    -1.9440 0.1079 0.05673 0.003218
    7    -2.3613 0.1221 0.08033 0.006453
Worst relative errors in SEs of simple contrasts (%):  -0.2 0.4 
Worst relative errors over *all* contrasts (%):  -1.2 0.5 

I now plot the results for "t0parsec" along with quasi-variance based 95% comparison intervals.

In [43]:
plot(model6.qvs)