Composite likelihood for joint analysis of multiple multistate processes via copulas.
A 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.
Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, 14642, United States.
Liqun
L
Diao
Department of Statistics and Actuarial Science,University of Waterloo,Waterloo, ON, N2L 3G1, Canada.
Richard J
RJ
Cook
D003627:Data Interpretation, Statistical; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D025241:Spondylarthritis / Q000453:epidemiology
Composite likelihood; Copula model; Interval censoring; Markov process; Multiplicative intensity; Multistate model