Literature DB >> 24719283

Composite likelihood for joint analysis of multiple multistate processes via copulas.

Liqun Diao1, Richard J Cook2.   

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.
© The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Composite likelihood; Copula model; Interval censoring; Markov process; Multiplicative intensity; Multistate model

Mesh:

Year:  2014        PMID: 24719283     DOI: 10.1093/biostatistics/kxu011

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  2 in total

1.  Multiple event times in the presence of informative censoring: modeling and analysis by copulas.

Authors:  Dongdong Li; X Joan Hu; Mary L McBride; John J Spinelli
Journal:  Lifetime Data Anal       Date:  2019-11-15       Impact factor: 1.588

2.  Clustered multistate models with observation level random effects, mover-stayer effects and dynamic covariates: modelling transition intensities and sojourn times in a study of psoriatic arthritis.

Authors:  Sean Yiu; Vernon T Farewell; Brian D M Tom
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2017-07-25       Impact factor: 1.864

  2 in total

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