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


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-12

AUTHORS

Lianqiang Qu, Liuquan Sun, Xinyuan Song

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. More... »

PAGES

609-633

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12561-018-9221-8

DOI

http://dx.doi.org/10.1007/s12561-018-9221-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106706021


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