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A flexible semi-Markov model for interval-censored data and goodness-of-fit testing

¹ Institute for Transplantation and Research in Transplantation and INSERM U643. 30 bd. Jean Monnet, Nantes 44093, France and Department of Biostatistics, Clinical Research Institute, University of Montpellier, 641 av. du doyen G. Giraud, Montpellier 34093, France
² Institute for Transplantation and Research in Transplantation and INSERM U643. 30 bd. Jean Monnet, Nantes 44093, France
³ Department of Biostatistics, Clinical Research Institute, University of Montpellier, 641 av. du doyen G. Giraud, Montpellier 34093, France

^* To whom correspondence should be addressed.

	Abstract

Multi-state approaches are becoming increasingly popular to analyse the complex evolution of patients with chronic diseases. For example, the evolution of kidney transplant recipients can be broken down into several clinical states. With this application in mind, we present a flexible semi-Markov model. The distribution functions are fitted to the durations in states and the relevance of the generalised Weibull distribution is shown. The corresponding likelihood function allows for interval censoring, i.e. the times of transitions and the sequences of states are not available during the elapsed times between two visits. The explanatory variables are introduced through the Markov chain and through the probability density functions of durations. A goodness-of-fit test is also defined to examine the stationarity of the semi-Markov model.

First published on September 2, 2008
Statistical Methods in Medical Research 2008, doi:10.1177/0962280208093889


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