A Joint Modeling Approach for Longitudinal Data with Informative Observation Times and a Terminal Event |
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Authors: | Lianqiang Qu Liuquan Sun Xinyuan Song |
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Institution: | 1.School of Mathematics and Statistics,Central China Normal University,Wuhan,People’s Republic of China;2.Institute of Applied Mathematics, Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing,People’s Republic of China;3.Department of Statistics,The Chinese University of Hong Kong,Hong Kong,People’s Republic of China |
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Abstract: | In this article, we propose a new joint modeling approach for the analysis of longitudinal data with informative observation times and a dependent terminal event. We specify a semiparametric mixed effects model for the longitudinal process, a proportional rate frailty model for the observation process, and a proportional hazards frailty model for the terminal event. The association among the three related processes is modeled via two latent variables. Estimating equation approaches are developed for parameter estimation, and the asymptotic properties of the proposed estimators are established. The finite sample performance of the proposed estimators is examined through simulation studies, and an application to a medical cost study of chronic heart failure patients is illustrated. |
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