Analysis of Chronic Disease Processes Based on Cohort and Registry Data
In this chapter, we review the types of observation schemes which arise in the analysis of data on chronic conditions from individuals in disease registries. We consider the utility of multistate modeling for such disease processes, and deal with both right-censored data and data arising from intermittent observation of individuals. The assumptions necessary to support standard likelihood or partial likelihood inference are highlighted and adaptations to deal with dependent censoring or dependent inspection are described and examined in simulation studies and through application.
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