Joint Analysis of Longitudinal Data With Informative Observation Times and a Dependent Terminal Event

In many longitudinal studies, repeated measures are often correlated with observation times. Also, there may exist a dependent terminal event such as death that stops the follow-up. In this article, we propose a new joint model for the analysis of longitudinal data in the presence of both informative observation times and a dependent terminal event via latent variables. Estimating equation approaches are developed for parameter estimation, and the resulting estimators are shown to be consistent and asymptotically normal. In addition, some graphical and numerical procedures are presented for model checking. Simulation studies demonstrate that the proposed method performs well for practical settings. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is provided.