Estimation and Assessment of Markov Multistate Models with Intermittent Observations on Individuals
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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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Jerald F. Lawless (2015). Estimation and Assessment of Markov Multistate Models with Intermittent Observations on Individuals. UWSpace. http://hdl.handle.net/10012/11013