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Estimation and assessment of markov multistate models with intermittent observations on individuals

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Abstract

Multistate models provide important methods of analysis for many life history processes, and this is an area where John Klein made numerous contributions. When individuals in a study group are observed continuously so that all transitions between states, and their times, are known, estimation and model checking is fairly straightforward. However, individuals in many studies are observed intermittently, and only the states occupied at the observation times are known. We review methods of estimation and assessment for Markov models in this situation. Numerical studies that show the effects of inter-observation times are provided, and new methods for assessing fit are given. An illustration involving viral load dynamics for HIV-positive persons is presented.

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Acknowledgments

This research was supported in part by a grant to J.F. Lawless from the Natural Sciences and Engineering Research Council of Canada. The authors thank Dr. Janet Raboud and the CANOC project, which was supported by funding from Emerging Team Grant 53444 (Dr. Robert Hogg, PI) from the Canadian Institutes of Health Research, for the HIV viral load data and for valuable discussion. They also thank Ker-ai Lee for assistance in managing the data, and Richard Cook and Brian Tom for helpful comments. Finally, the authors are grateful for comments by two anonymous reviewers which led to substantial improvements in the paper.

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  1. Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada

    J. F. Lawless & N. Nazeri Rad

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  1. J. F. Lawless
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  2. N. Nazeri Rad
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Correspondence to J. F. Lawless.

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Lawless, J.F., Nazeri Rad, N. Estimation and assessment of markov multistate models with intermittent observations on individuals. Lifetime Data Anal 21, 160–179 (2015). https://doi.org/10.1007/s10985-014-9310-z

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  • DOI: https://doi.org/10.1007/s10985-014-9310-z

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