A Joint Modeling Approach for Longitudinal Data with Informative Observation Times and a Terminal Event

Lianqiang Qu (), Liuquan Sun () and Xinyuan Song ()
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Lianqiang Qu: Central China Normal University
Liuquan Sun: Chinese Academy of Sciences
Xinyuan Song: The Chinese University of Hong Kong

Statistics in Biosciences, 2018, vol. 10, issue 3, No 7, 609-633

Abstract: 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.

Keywords: Dependent terminal event; Estimating equations; Frailty; Informative observation; Longitudinal data; Mixed effects (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s12561-018-9221-8

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