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Analysis of interval-censored data from clustered multistate processes: application to joint damage in psoriatic arthritis

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Summary. 

A conditionally Markov multiplicative intensity model is described for the analysis of clustered progressive multistate processes under intermittent observation. The model is motivated by a long-term prospective study of patients with psoriatic arthritis with the aim of characterizing progression of joint damage via an irreversible four-state model. The model accommodates heterogeneity in transition rates between different individuals and correlation in transition rates within patients. To do this we introduce subject-specific multivariate random effects in which each component acts multiplicatively on a specific transition intensity. Through the association between the components of the random effect, correlations in transition intensities are accommodated. A Monte Carlo EM algorithm is developed for estimation, which features closed form expressions for estimators at each M-step.
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Keywords: Conditionally Markov model; Interval-censored data; Monte Carlo EM algorithm; Progressive multistate process; Psoriatic arthritis

Document Type: Research Article

Affiliations: 1: Institute for Clinical Evaluative Sciences, Toronto, and Samuel Lunenfeld Research Institute, Toronto, Canada 2: University of Waterloo, Canada

Publication date: 2008-12-01

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