Analysis of Chronic Disease Processes Based on Cohort and Registry Data

Richard J. Cook () and Jerald F. Lawless
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Richard J. Cook: University of Waterloo, Department of Statistics and Actuarial Science
Jerald F. Lawless: University of Waterloo, Department of Statistics and Actuarial Science

Chapter Chapter 15 in Mathematical and Statistical Applications in Life Sciences and Engineering, 2017, pp 305-325 from Springer

Abstract: Abstract 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.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-10-5370-2_15

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DOI: 10.1007/978-981-10-5370-2_15

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