Abstract
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 article we show how such repeated measures data can be modeled 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 modeling.
