Affiliation:
1. Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON N2L 3G1, Canada
Abstract
Summary
Multistate models provide a powerful framework for the analysis of life history processes when the goal is to characterize transition intensities, transition probabilities, state occupancy probabilities, and covariate effects thereon. Data on such processes are often only available at random visit times occurring over a finite period. We formulate a joint multistate model for the life history process, the recurrent visit process, and a random loss to follow-up time at which the visit process terminates. This joint model is helpful when discussing the independence conditions necessary to justify the use of standard likelihoods involving the life history model alone and provides a basis for analyses that accommodate dependence. We consider settings with disease-driven visits and routinely scheduled visits and develop likelihoods that accommodate partial information on the types of visits. Simulation studies suggest that suitably constructed joint models can yield consistent estimates of parameters of interest even under dependent visit processes, providing the models are correctly specified; identifiability and estimability issues are also discussed. An application is given to a cohort of individuals attending a rheumatology clinic where interest lies in progression of joint damage.
Funder
Natural Sciences and Engineering Research Council of Canada
Canadian Institutes of Health Research
Publisher
Oxford University Press (OUP)
Subject
Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability
Cited by
12 articles.
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