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Large-scale, cross-sectional government datasets; research published and recent developments. Jo Wathan Data Support Economic and Social Data Service (Government) Cathie Marsh Centre for Census and Survey Research University of Manchester


  1. Large-scale, cross-sectional government datasets; research published and recent developments. Jo Wathan Data Support Economic and Social Data Service (Government) Cathie Marsh Centre for Census and Survey Research University of Manchester UK Jo.wathan@manchester.ac.uk http://www.esds.ac.uk/government

  2. ESDS Government • Economic and Social Data Service is the leading data dissemination and support service for social data in the UK. Started Jan ‘03 • Distributed service, involving 4 organisations at 2 sites in the UK • ESDS Government is one of 4 specialist services. It deals with large-scale cross-sectional continuous surveys – Academic service funded by Economic and Social Research Council – Data archiving and dissemination done by the UK Data Archive (download/Nesstar) – User support and outreach done by the Centre for Census and Survey Research – Data comes from the Office for National Statistics or National Centre for Social Research

  3. Which surveys? • General Household Survey • Labour Force Survey • Family Resources Survey • Expenditure and Food Survey (previously the National Food Survey and Family Expenditure Survey) • ONS Omnibus Survey • National Travel Survey • Time Use Survey • British Crime Survey/Scottish Crime Survey • British Social Attitudes/Scottish Social Attitudes/Northern Ireland Life & Times/Young People’s Social Attitudes • Health Survey for England/Wales/Scotland • Survey of English Housing (England only)

  4. What is the data like? • Survey microdata • Large sample sizes (but smaller than the SARs) • Continuous surveys – always up-to-date • Cross-sectional (although the LFS has a 5- quarter panel element, GHS goes longitudinal this year) • Specialist topic surveys – more depth than the Census • Freely available to academics via ESDS

  5. Increased data use: Jan 02-now (ESDS started Jan 03) 10000 9000 8000 Other 7000 FES/NFS/EFS 6000 5000 BCS 4000 HSE 3000 2000 GHS 1000 LFS 0 2002(1) 2002(2) 2003(1) 2003(2) 2004(1) 2004(2)

  6. How are the data used? To provide nationally representative results, with the flexibility of microdata: • Analyses looking at change over time – Repeated cross-sections – Pseudo-cohort studies • To look at sub-populations – Large sample sizes – Many datasets can be pooled due to relative consistency in content and method over time • Hierarchical data for household analyses • To provide users with the scope to operationalise concepts differently and use more sophisticated modelling

  7. Change over time • Data well suited – emphasis SMOKING AND SOCIAL CLASS - MEN on stability and comparability 45 • Straightforward trends; e.g. 40 – Smoking by class (Marmot 35 2003) 30 25 – Smoking prevalence by month % 20 (Jarvis 2003) 15 – Attitudes to homosexuality 10 (Crocket and Voas 2003) 5 • Pseudo cohort analyses 0 1994 1995 1996 1997 1998 1999 2000 2001 – Women’s access to pensions by partnership (Ginn 2003) year – Alcohol consumption by age Source:HSE all sc I&II sc IV&V (Kemm 2003) – Changing risk factors for divorce by year of marriage (Chan & Halpin 2005)

  8. Representative samples of subpopulations • Samples vary but can be large: – Labour Force Survey: c.60k households – Family Resources survey: c.27k households – British Crime Survey: c. 33k individuals • Pool to increase sample size of small subpopulations – e.g. individual ethnic groups – 12 years pooled of LFS to look at women’s employment by ethnic group (Dale et. Al 2005) – 3 years of FRS to look at women’s pension chances by ethnic group (Ginn and Arber 2001) • Health Survey contains subgroup boosts – 1999 Ethnic minority boost allow analysis of obesity by ethnic group (Saxena et. Al. 2004)

  9. Using hierarchy to look within households • Workless Household ID Household type Households (Dickens et.al, 2000) Person 1 Person 2 Person 3 • Educational 40 years 42 14 Female Male Male homogamy in Working Unemployed Student Britain & Ireland Workless households (source FES, various years (Halpin 2003) 1968-1996) • Impact of 25 parenthood/ Percentage (of present partnership 20 working age hoh) workless households 15 children in workless 10 households 5 0 68 70 72 74 76 78 80 82 84 86 88 90 92 94 96 Year

  10. ESDS Government Outreach and Support • Help-desk • User Groups • Annual Research Conference • Newsletter • Vital stats GIS interface • Interface between Government and Users • Themed materials and training – Training workshops and publicity events – Production of teaching datasets – Web-based materials

  11. Workshop and Events Introductory workshops (inc. those joint with SARs workshops) Joint workshops with other ESDS services Methods Research conferences Dataset user groups Other presentations Posters

  12. Data - value added • Annual teaching dataset produced – With documentation – Based around annual theme • Information about comparing data over time – Derived variables produced where necessary – User-generated derived variables QAd and made available

  13. Resources to support users • Thematic Guides • FAQs & Starting Analysis Guides • Methodological Guides – SPSS, Stata – Guide to weighting • Publications database • Biannual newsletter • Links to other web resources

  14. CommonGIS Interface for Vital Statistics

  15. Help-desk • 174 Queries in the last year • Range of different ranges of complexity: – How do I get access to the HSE? – What are social classes written as roman numerals? – Why do my sample sizes increase if I weight? – Should I apply weights if I’m modelling? – The sample size for matched LFS data seem wrong – The household identifiers are missing from an early LFS • Help desk involves collaboration with UKDA and ONS

  16. Interface between data depositors and users • Organise User Groups for data producers to meet users • Awareness and consultation role in developments – General Household Survey (Longitudinal) – Continuous Population Survey • Data access e.g. Special Conditions – Response to increased concern about confidentiality and withdrawal of some data – Negotiation of tighter conditions to permit access to data which poses greater confidentiality concerns – Access to information on date of birth, local authority district etc.

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