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Abstract Details

Activity Number: 114
Type: Topic Contributed
Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #306758
Title: Joint Analysis of Survival Time and Longitudinal Categorical Outcomes
Author(s): Jaeun Choi*+ and Jianwen Cai and Donglin Zeng
Companies: The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill and The University of North Carolina at Chapel Hill
Address: CB#7420, Gillings School of Global Public Health, Chapel Hill, NC, 27599,
Keywords: Simultaneous modeling ; Stratified Cox proportional hazards model ; Generalized linear mixed model ; Maximum likelihood estimator ; Random effect ; EM algorithm
Abstract:

In biomedical studies, researchers are often interested in the relationship between patients' characteristics or risk factors and both survival time and longitudinal categorical outcomes. We propose to jointly model the survival time with a stratified Cox proportional hazards model and longitudinal categorical outcomes with a generalized linear mixed model. Random effects are introduced to account for the dependence between survival time and longitudinal outcomes due to unobserved factors. The EM algorithm and the observed information matrix are used for the point and asymptotic variance estimation of the parameters in the proposed models. Asymptotic properties of the proposed maximum likelihood estimators are established. Finite sample properties are assessed via simulations. We illustrate our approach with a liver transplantation data set and a cytomegalovirus disease data set.


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