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

Author

Listed:
  • Lianqiang Qu

    (Central China Normal University)

  • Liuquan Sun

    (Chinese Academy of Sciences)

  • Xinyuan Song

    (The Chinese University of Hong Kong)

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.

Suggested Citation

  • Lianqiang Qu & Liuquan Sun & Xinyuan Song, 2018. "A Joint Modeling Approach for Longitudinal Data with Informative Observation Times and a Terminal Event," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 609-633, December.
    • Handle: RePEc:spr:stabio:v:10:y:2018:i:3:d:10.1007_s12561-018-9221-8
    DOI: 10.1007/s12561-018-9221-8
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    References listed on IDEAS

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    1. Liuquan Sun & Xinyuan Song & Jie Zhou & Lei Liu, 2012. "Joint Analysis of Longitudinal Data With Informative Observation Times and a Dependent Terminal Event," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 688-700, June.
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    14. Ryu, Duchwan & Sinha, Debajyoti & Mallick, Bani & Lipsitz, Stuart R. & Lipshultz, Steven E., 2007. "Longitudinal Studies With Outcome-Dependent Follow-up: Models and Bayesian Regression," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 952-961, September.
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