Composite likelihood for joint analysis of multiple multistate processes via copulas
Abstract
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.
Collections
Cite this version of the work
Richard J. Cook, Liqun Diao
(2014).
Composite likelihood for joint analysis of multiple multistate processes via copulas. UWSpace.
http://hdl.handle.net/10012/10213
Other formats