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dc.contributor.authorCook, Richard J.
dc.contributor.authorDiao, Liqun 20:45:24 (GMT) 20:45:24 (GMT)
dc.descriptionThis is a pre-copyedited, author-produced PDF of an article accepted for publication in Biostatistics following peer review. The version of record Biostat (2014) 15 (4): 690-705 first published online April 9, 2014 doi:10.1093/biostatistics/kxu011 is available online at:
dc.description.abstractA copula-based model is described which enables joint analysis of multiple progressive multistate processes. Unlike intensity-based or frailty-based approaches to joint modeling, the copula formulation proposed herein ensures that a wide range of marginal multistate processes can be specified and the joint model will retain these marginal features. The copula formulation also facilitates a variety of approaches to estimation and inference including composite likelihood and two-stage estimation procedures. We consider processes with Markov margins in detail, which are often suitable when chronic diseases are progressive in nature. We give special attention to the setting in which individuals are examined intermittently and transition times are consequently interval-censored. Simulation studies give empirical insight into the different methods of analysis and an application involving progression in joint damage in psoriatic arthritis provides further illustration.en
dc.description.sponsorshipNatural Sciences and Engineering Research Council || RGPIN/155849 Canadian Institutes for Health Research (FRN 13887)en
dc.publisherOxford Journalsen
dc.titleComposite likelihood for joint analysis of multiple multistate processes via copulasen
dc.title.alternativeComposite likelihood for multiple multistate processesen
dcterms.bibliographicCitationDiao L and Cook RJ (2014). Biostatistics, 15 (4): 690-705. DOI:10.1093/biostatistics/kxu011en
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2Statistics and Actuarial Scienceen

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