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

Yue Liu; Lei Liu; Jianhui Zhou

doi:10.1016/j.csda.2015.05.007

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

Yue Liu, Lei Liu, Jianhui Zhou

Research output: Contribution to journal › Article › peer-review

21 Scopus citations

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.

Original language	English
Pages (from-to)	40-50
Number of pages	11
Journal	Computational Statistics and Data Analysis
Volume	91
DOIs	https://doi.org/10.1016/j.csda.2015.05.007
State	Published - Jun 20 2015

Keywords

Counting process
Dependent censoring
Frailty model
Gaussian quadrature
Informative dropout
Mixed effects model
Mixture model
Proportional hazards model
Survival analysis

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10.1016/j.csda.2015.05.007

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title = "Joint latent class model of survival and longitudinal data: An application to CPCRA study",

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, Dependent censoring, Frailty model, Gaussian quadrature, Informative dropout, Mixed effects model, Mixture model, Proportional hazards model, Survival analysis",

author = "Yue Liu and Lei Liu and Jianhui Zhou",

year = "2015",

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doi = "10.1016/j.csda.2015.05.007",

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T1 - Joint latent class model of survival and longitudinal data

T2 - An application to CPCRA study

AU - Liu, Yue

AU - Liu, Lei

AU - Zhou, Jianhui

PY - 2015/6/20

Y1 - 2015/6/20

N2 - 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.

AB - 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.

KW - Counting process

KW - Dependent censoring

KW - Frailty model

KW - Gaussian quadrature

KW - Informative dropout

KW - Mixed effects model

KW - Mixture model

KW - Proportional hazards model

KW - Survival analysis

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U2 - 10.1016/j.csda.2015.05.007

DO - 10.1016/j.csda.2015.05.007

M3 - Article

AN - SCOPUS:84934971509

SN - 0167-9473

VL - 91

SP - 40

EP - 50

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

ER -

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

Abstract

Keywords

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