A flexible procedure for analyzing longitudinal event histories using a multilevel model
- Understanding Statistics, 3, 127-153
Event history or survival models are applicable to outcomes that are measures of duration, for example the length of employment periods or times to death after medical treatment. When individuals are grouped within institutions such as firms or clinics the resulting multilevel structure also needs to be incorporated into the model. An important application is where individuals are the ‘higher level’ units and they experience repeated durations, such as lengths of partnerships. In this paper we show how such repeated measures data can be modelled using a flexible discrete time event history model that incorporates individual level random effects. The model is applied to the analysis of partnership episodes for adult members of the National Child Development Study followed up between the ages of 16 and 33. The exposition will not assume a detailed knowledge of event history modelling.
- Number of levels
- Model data structure
- Response types
- Multivariate response model?
- Longitudinal data?
- Substantive discipline
Important paper setting out methodology for flexible multilevel survival modelling that can be carried out in MLwiN.
- Paper submitted by
- Harvey Goldstein, Graduate School of Education, University of Bristol, email@example.com