Models for recurrent events, multiple states and interdependent events, current events, multiple states and interdependent events

Professor Fiona Steele, University of Bristol

Most life course events can be experienced more than once by an individual, and recurrent events can be viewed as a having a hierarchical structure with multiple 'at risk' episodes nested within individuals. Further complexity arises when the occurrence of an event may mark the transition to a different state (e.g. formation of the first union marks a transition from the 'single' to the 'marriage' or 'cohabitation' state). This course will consider multilevel (random effects) models for recurrent events and transitions between multiple states, with a focus on discrete-time methods.

Another important issue in event history analysis is that covariates (especially those with time-varying values) are potentially endogenous, i.e. jointly determined with the timing of the event of interest. For example, in an analysis of the impact of childbearing on women's employment, time-varying indicators of the presence and number of children are outcomes of a process that may have similar unmeasured determinants to employment transitions. Another example where endogeneneity is a particular concern is in evaluations of selective interventions. This course will introduce simultaneous equation (multiprocess) models that allow for such dependencies.


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Course materials

Recurrent events, multiple states and interdependent events (PDF, 683kB)

Further reading

Recurrent events

Transitions between multiple states

Multiprocess models for interdependent events

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