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A joint modeling approach for analyzing marker data in the presence of a terminal event

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  • Jie Zhou
  • Xin Chen
  • Xinyuan Song
  • Liuquan Sun

Abstract

In many medical studies, markers are contingent on recurrent events and the cumulative markers are usually of interest. However, the recurrent event process is often interrupted by a dependent terminal event, such as death. In this article, we propose a joint modeling approach for analyzing marker data with informative recurrent and terminal events. This approach introduces a shared frailty to specify the explicit dependence structure among the markers, the recurrent, and terminal events. Estimation procedures are developed for the model parameters and the degree of dependence, and a prediction of the covariate‐specific cumulative markers is provided. The finite sample performance of the proposed estimators is examined through simulation studies. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is illustrated.

Suggested Citation

  • Jie Zhou & Xin Chen & Xinyuan Song & Liuquan Sun, 2021. "A joint modeling approach for analyzing marker data in the presence of a terminal event," Biometrics, The International Biometric Society, vol. 77(1), pages 150-161, March.
    • Handle: RePEc:bla:biomet:v:77:y:2021:i:1:p:150-161
    DOI: 10.1111/biom.13260
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    References listed on IDEAS

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