Survival analysis provides a natural conceptual framework for considering risk.However, survey data on age of onset typically possess measurement error and sample design complexities that are absent from the usual settings in which survival analysis is applied.The authors describe a random effects discrete time survival model that addresses these problems.They illustrate its use by an analysis of retrospective report data on the age of onset of smoking from two cross-sectional school-based studies.
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