Migration data
The data are derived from a large retrospective survey of life and work histories carried out in 1986 under the Social Change and Economic Life Initiative (SCELI). The data contain the migration histories of 348 males aged 20 to 60, starting from the completion of education up to 1985. The data set is longitudinal, with one observation for each individual per calendar year. There are a total of 6349 annual observations. The response variable is binary, indicating for each individual for each year whether there was a migration move. The explanatory variables include age, calendar year, duration of stay at each address and information on family and work histories.
Modelling migration histories example

Youth data
The data set contains a random sample of 800 young people taken from the Youth Cohort Study of England and Wales, Cohort 3. The data were collected three times at yearly intervals in the late 1980s when the young people were 16 to 19. There are therefore a total of 2400 annual observations. The response variable is a four category hierarchical outcome, indicating for each year whether the young person was in education, unemployed, in employment or training, or out of the labour market. The explanatory variables are educational attainment, gender, ethnicity, and parental social class and education.
Post-compulsory education routes example

Education data
This data set contains GCSE exam scores on 4059 pupils in 65 inner london schools. The data are for pupils sitting GCSE exams in 1990. There are also intake ability measures on the pupils at age 11(entry into secondary school). Pupil gender and school gender(boys school, girls school or mixed school) are also recorded.
Education example

Mortality data
The data are taken from the local mortality datapack and detail deaths from all causes in England and Wales in the period 1979 to 1992. The data comprise the Standardised Mortality Ratio (SMR) for each of 403 districts in the 54 counties of England and Wales, with one observation for each year from 1979 to 1992. (The SMR is the ratio of the observed number of deaths in an area to the number of deaths that would be expected if national age- and sex- specific death rates were applied to each area.) Our model therefore has three levels: years nested within districts in counties. We also have information on the classification of the district into one of six types: rural areas, prospering areas, maturer areas, urban centres, mining and industrial
Mortality example