Lifetime Data Anal - A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects.

Tópicos

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Resumo

This article studies a general joint model for longitudinal measurements and competing risks survival data. The model consists of a linear mixed effects sub-model for the longitudinal outcome, a proportional cause-specific hazards frailty sub-model for the competing risks survival data, and a regression sub-model for the variance-covariance matrix of the multivariate latent random effects based on a modified Cholesky decomposition. The model provides a useful approach to adjust for non-ignorable missing data due to dropout for the longitudinal outcome, enables analysis of the survival outcome with informative censoring and intermittently measured time-dependent covariates, as well as joint analysis of the longitudinal and survival outcomes. Unlike previously studied joint models, our model allows for heterogeneous random covariance matrices. It also offers a framework to assess the homogeneous covariance assumption of existing joint models. A Bayesian MCMC procedure is developed for parameter estimation and inference. Its performances and frequentist properties are investigated using simulations. A real data example is used to illustrate the usefulness of the approach.

Resumo Limpo

articl studi general joint model longitudin measur compet risk surviv data model consist linear mix effect submodel longitudin outcom proport causespecif hazard frailti submodel compet risk surviv data regress submodel variancecovari matrix multivari latent random effect base modifi choleski decomposit model provid use approach adjust nonignor miss data due dropout longitudin outcom enabl analysi surviv outcom inform censor intermitt measur timedepend covari well joint analysi longitudin surviv outcom unlik previous studi joint model model allow heterogen random covari matric also offer framework assess homogen covari assumpt exist joint model bayesian mcmc procedur develop paramet estim infer perform frequentist properti investig use simul real data exampl use illustr use approach

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