1. The Samples of Anonymised Records: Understanding Individual differences Mark Brown

2. Before 1991, Census data only released as predefined tables Academic arguments for importance of microdata - individual records –not constrained to fixed tables –allows multivariate analysis Background to the 1991 SARs

3. The 1991 Samples of Anonymised Records Release of two samples of microdata - a major innovation of 1991 Census Consist of individual and household records for full range of census variables 2% Individual SAR: 1.1m individuals 1% Household SAR: 200k households non-overlapping and stratified by geography GB & NI SARs produced separately

4. Research value of the SARs This talk highlights some of key qualities of SARs as a research tool for more detailed summary of research applications see –SARS website: http://www.ccsr.ac.uk/sars/use/findings –CHCC teaching and learning module: http://www.chcc.ac.uk/overview/faq13/frame.html –forthcoming paper in British Journal of Sociology by Yaujun Li

5. 200K Households, 1.1 million Individuals Allows analysis of small subgroups e.g. minority ethnic groups A large sample

6. Other examples.. health status of elderly people educational participation of 16-19 years olds research that needs to differentiate specific occupations (1991 Household SAR: 358 occupations) characteristics of migrants A large sample

7. Individual SAR: –278 SAR areas (with minimum 120K population) Allows most Local Authorities to be identified - especially in urban areas Allows place to be included in analysis Analysis of individual versus area effects - application of multilevel modelling techniques Fine geographical definition

8. Including place in analysis e.g. in study of unemployment Fieldhouse and Gould (1998) use SARS to show that the type of local labour market does affect the probability of unemployment over and above the effect of individual characteristics such as age and educational qualifications. Fieldhouse and Tranmer (forthcoming) use the area classification information on the SAR to examine the relative importance of the individual, the type of neighbourhood of residence, and the local labour market in which one lives in explaining variations in unemployment risk. Fine geographical definition

9. Household file includes individual records for all members of selected households Allows detailed analysis of household and family structures and the interrelationships within them. User defined classifications e.g. of living arrangements of young people Again, the large sample size affords rare opportunity to focus on relatively small sub-sections of the population, such as the young or the elderly, or minority ethnic groups. See for example Holdsworth and Dale 1997. –Ethnic homogeneity within households –Ethnic differences in female employment Individuals in households

10. Ethnic differences in womens employment over the life course (Dale and Holdsworth)

11. Important omission from household surveys Inclusion may be of particular importance e.g. in study of the elderly - especially health differences e.g. Glaser et al (1997) Including the institutional population

12. Working towards the 2001 SARs ONS adopt tougher position on confidentiality, forcing major revisions to original specification for 2001 - loss of variable detail e.g. no geography on individual SAR further confidentiality assessment work/ consultation over changes causes major delays. Current due date of Individual SAR Sept 04. Latest at http://www.ccsr.ac.uk/sars/news/ Exploring potential for research access to more detailed file via safe setting at ONS On going discussion about middle way Additional issues for Scotland

13. Using the SARs Access via Census registration Service (one stop shop) Documentation and software guides online Download to a variety of software packages SPSS, Stata and SAS users supported Nesstar can be used online to do straightforward analyses NSDstat available for users without software More info and support at http://www.ccsr.ac.uk/sarshttp://www.ccsr.ac.uk/sars