BSAS/BCS Longitudinal Datasets: A Training Workshop

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Presentation transcript:

BSAS/BCS Longitudinal Datasets: A Training Workshop Stephen Farrall, Emily Gray, Will Jennings Manchester, May 2015

Workshop Outline 1: Intro to the project 2: Data sources 3: The datasets we have constructed 4: Analyses one could undertake 5: Possible extensions to dataset 6: Getting and using the datasets 7: Syntax and do files 8: Data sandpit (aka ‘playtime’) 10.30-12.00 12.45-13.45 14.00-15.30

Project Outline ESRC grant award no ES/K006398/1 Our aim is to assess what Thatcherite social and economic policies did to crime ‘downstream’. Uses ideas from political science (agenda setting, historical institutionalism) to bring fresh thinking to attempts to explain rises/falls in crime.

Project Outline Our earlier analyses had used national level data (GDP, Gini, recorded crime). Wanted to: a) use attitudinal data as well, b) explore subgroup experiences and c) incorporate self-reported data

Project Outline This meant ... Reviewing the existing datasets (ESRC funded project 2008) Working out how to interrogate the datasets Building the dataset needed (current ESRC award).

Methodological challenges Complex relationship between crime and economic factors. Need to embed models of the crime-economy link in a wider understanding of social, economic and political changes.

Methodological challenges Data preparation took +15mths (and is on-going!) Need to code variable names, values, check question wordings, consistency over time. Changes in survey designs over time too. Use of historical data (in effect).

Original Sources of Data BCS (CSEW) BSA BES (‘Continuous Monitoring Survey’) Aggregate datasets from a range of official sources (e.g. police, probation staffing, recorded crime, socio-economic data). No boosters samples (ethnic minorities, 12-15 year olds).

Datasets include ... Fear of crime, victimisation, local ASB, CJS ‘effectiveness’, crime prevention measures, crime rates, interviewer assessments. Social/political attitudes, voting, political engagement, trust, newspaper readership. Usual socio-demographics (age, tenure, gender region, on benefits) Range of official data (recorded crime).

Our philosophy The data isn’t ours’ - it is yours’ as much as it ours’. The data is there to be used any way you wish (within the confines of sampling, appropriate analyses, etc) but please do heed the health warnings below! Please also encourage people who want to use the data to download it direct from the UKDA – this means that more precise data on usage can be collected for the UKDA’s records.

Health warnings We don’t have the resources to support users after the end of the grant. Sorry! We can’t respond to queries about the ORIGINAL surveys (we didn’t design them). All datasets have limitations – this is no different. Secondary data analyses is limited by preoccupation of earlier generations of social sciences (and then ourselves too). Missing variables. Caps for victimisation.

How the BCS data is structured… Data recorded as individual observations in rows. Each observation includes the relevant BCS sweep, year and sourcefile (UKDS)…

How the BCS data is structured… Each observation includes associated demographic data (sometimes recoded)…

How the BCS data is structured… Each observation includes responses to a range of questions on worry about crime, victimisation, attitudes on punishment.

How the BCS data is structured… Observations on victimisation include dichotomous (yes/no) and frequency measures.

How the BCS data is structured… Data also includes summary measures of victimisation; across all categories and for specific categories.

How the BSA data is structured… Data for the BSA is structured much the same… Slight differences with the BCS: includes measure of social class, more attitudinal questions…

How the data is structured… Possibilities for data manipulation include: Within- and between-year comparisons. Between-survey comparisons. Individual propensities vs. national trends.

Q&A Session I Questions about the datasets? (We’ll look at the sorts of analyses in the next session, after lunch).

Victimisation Raw Data Inspection of the raw BCS data. Example:

Fear of Crime Raw Data Another example:

Fear of Crime Raw Data Disaggregate by housing tenure (renting):

Analyses possible II More complex individual level Age-period-cohort (APC) (attitudes) Conditional formatting Multi-level modelling (years; regions – too few?) ‘Pooled’ rare populations (male DV victims)

Age, period & cohort analysis. Example of ‘teenagers hanging around – perceived as a problem by political generations. Year of birth 1910-1990.

Conditional formatting Conditional formatting. Is the gap between the rich and poor too large (high values agree) Britain 1983-2012, by age.

Analyses possible I Individual level Linear/logistic regression (attitudes) Neg. binomial/Poisson regression (victimisation)* Factor analyses Path/structural equation modelling T-tests Cross-tabulations * Raw counts for victimisation included, but capped at 97 (original files do this – sorry!).

Analyses possible III Aggregated levels Time series models Structural equation model time series Dynamic factor analyses Latent growth modelling

Data Time Series Possible to aggregate the individual-level data over time to plot trends. Take example of fear of crime:

Data Time Series Remember ‘fear of crime’ is measured on scale from 1=very safe … 4=very unsafe

Data Time Series Take another example, this time from the BSA, on attitudes towards sentencing, by social class.

Data Time Series Question is agree/disagree with ‘stiffer sentences’ (III.M, IV & V are working and manual class).

Possible extensions Extend future years by appending these Include Vs we didn’t collect (other attitudes in BSA, for example) Add other aggregate levels Vs from other datasets by year (NHS data on wounding, for example) Create new Vs by collapsing/combining existing Vs (e.g. single people w/ a car)

Possible extensions Do the same thing with the BCS EM boosters. Do the same thing with Scottish Crime Surveys (few and far between). Do the same thing with other datasets?

Getting the Data Lodged with UKDA in late 2015, early 2016. Free to download. Please cite ESRC award no. ES/006398K/1, Farrall = PI; 2013-2015 AND Jennings, W., Gray, E. Hay, C. and Farrall, S. (2015) Collating Longitudinal Data on Crime, Victimisation and Social Attitudes in England and Wales: A New Resource for Exploring Long-term Trends in Crime, British Journal of Criminology. THANK YOU!

What will I get? The data (!). Individual level. Stata and SPSS versions will be given to UKDA. Syntax and do files will be made available. Access spreadsheet for codebook. Original study numbers (so you can explore original questionnaires)

What will I get? BCS: approx 600,000 Respondents BCS: approx. 200 variables BCS: 20 sweeps (1982 to 2012) BSA: approx 90,000 Respondents (a tiddler!) BSA: approx. 120 variables BSA: 28 sweeps (1983-2012, only years missing are 1988 and 1992)

What will I get? BES-CMS: approx. 124,110 Respondents BES-CMS: approx. 63 variables BES-CMS: sweeps (2004 to 2013) Aggregate data: all sorts of things! Socio-economic data: house repossessions, kids in care, divorce rate, income inequality/poverty rates, inflation, unemployment rate (by region), etc. Political data: parliamentary questions, public and policy agendas.

Useful Resources Syntax and do files allow you to replicate our analyses, and also to mimic it (replacing our code with new V names). Data is export (in part or whole) to other databases. Webpage: http://www.shef.ac.uk/law/research/projects/crimetrajectories Email newsletter: s.farrall@sheffield.ac.uk

Potential Uses Data analyses! PhD and Masters theses UG teaching (Q-Step programme) Training non-academics in various statistical techniques Some trends revisited/picked up by ESS

Session II: Q&A Questions about the possible data analyses? (We may not be able to help with Qs about the techniques themselves if they are too specific, but we will try to).

Sandpit (‘play time’) But before we start ...

What will I get today? 10% sample of survey datasets for BSA, BCS, BES. Why 10%? Faster to process. We need to supervise full release. Please do tell us if you spot anything odd looking. No weights for BCS (these are complex and we are still working on them) . Access database. A chance to play with the 10% dataset.

Session III: Q&A Questions about the project, datasets or analyses?