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Lifetime Data Anal. 2007 Mar;13(1):91-117.

Asymptotic theory for the Cox semi-Markov illness-death model.

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  • 1Department of Biometrics and Reporting, Centocor, Inc., 200 Great Valley Parkway, Mailstop C-4-1, Malvern, PA 19355, USA. yshu@cntus.jnj.com

Abstract

Irreversible illness-death models are used to model disease processes and in cancer studies to model disease recovery. In most applications, a Markov model is assumed for the multistate model. When there are covariates, a Cox (1972, J Roy Stat Soc Ser B 34:187-220) model is used to model the effect of covariates on each transition intensity. Andersen et al. (2000, Stat Med 19:587-599) proposed a Cox semi-Markov model for this problem. In this paper, we study the large sample theory for that model and provide the asymptotic variances of various probabilities of interest. A Monte Carlo study is conducted to investigate the robustness and efficiency of Markov/Semi-Markov estimators. A real data example from the PROVA (1991, Hepatology 14:1016-1024) trial is used to illustrate the theory.

PMID:
17115258
[PubMed - indexed for MEDLINE]

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