Multistate Models in Epidemiology
 D. Commenges
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I first discuss the main assumptions which can be made for multistate models: the timehomogeneity and semiMarkov assumptions, the problem of choice of the time scale, the assumption of homogeneity of the population and also assumptions about the way the observations are incomplete, leading to truncation and censoring. The influence of covariates and different durations and timedependent variables are synthesized using explanatory processes, and a general additive model for transition intensities presented. Different inference approaches, including penalized likelihood, are considered. Finally three examples of application in epidemiology are presented and some references to other works are given.
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 Title
 Multistate Models in Epidemiology
 Journal

Lifetime Data Analysis
Volume 5, Issue 4 , pp 315327
 Cover Date
 19991201
 DOI
 10.1023/A:1009636125294
 Print ISSN
 13807870
 Online ISSN
 15729249
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 multistate models
 epidemiology
 survival data
 Markov models
 semiMarkov models
 timedependent variables
 Industry Sectors
 Authors

 D. Commenges ^{(1)}
 Author Affiliations

 1. Université de Bordeaux 2, 146, rue Léo Saignat, 33076, Bordeaux Cedex, France