Joint modeling of longitudinal data with a dependent terminal event

Sui He, Ting Du and Liuquan Sun

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 3, 813-835

Abstract: Longitudinal data often arise in longitudinal follow-up studies, and there may exist a dependent terminal event such as death that stops the follow-up. In this article, we propose a new joint modeling for the analysis of longitudinal data with informative observation times via a dependent terminal event and two latent variables. Estimating equations are developed for parameter estimation, and asymptotic properties of the resulting estimators are established. In addition, a generalization of the joint model with time-varying coefficients for the longitudinal response variable is considered, and goodness-of-fit methods for assessing the adequacy of the model are also provided. The proposed method works well in our simulation studies, and is applied to a data set from a bladder cancer study.

Date: 2016
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DOI: 10.1080/03610926.2013.851237

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