Joint latent class model of survival and longitudinal data: An application to CPCRA study

Yue Liu, Lei Liu and Jianhui Zhou

Computational Statistics & Data Analysis, 2015, vol. 91, issue C, 40-50

Abstract: There has been an increasing interest in the joint analysis of repeated measures and time to event data. In many studies, there could also exist heterogeneous subgroups. Thus a new model is proposed for the joint analysis of longitudinal and survival data with underlying subpopulations identified by latent class model. Within each latent class, a joint model of longitudinal and survival data with shared random effects is adopted. The proposed model is applied to Terry Beirn Community Programs for Clinical Research on AIDS study (CPCRA) to characterize the underlying heterogeneity of the cohort and to study the relation between longitudinal CD4 measures and time to death. The proposed model is desirable when the heterogeneity among subjects cannot be ignored and both the longitudinal and survival outcomes are of interest.

Keywords: Counting process; Proportional hazards model; Gaussian quadrature; Mixture model; Dependent censoring; Informative dropout; Frailty model; Mixed effects model; Survival analysis (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:91:y:2015:i:c:p:40-50

DOI: 10.1016/j.csda.2015.05.007

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