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Recurrent Events Analysis in the Presence of Terminal Event and Zero-recurrence Subjects

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  • Xiaobing Zhao
  • Jinglong Wang
  • Xian Zhou
  • Zhongyi Zhu

Abstract

Recurrent event data are often encountered in longitudinal follow-up studies related to biomedical science, econometrics, reliability, and demography. In many situations, a terminal event such as death can happen during the follow-up period that precludes further recurrences. In this article, we will review some existing models for recurrent event with information censoring, and then extend them to allow zero-recurrence subjects as well as a terminal event. Estimating equations and partial likelihood are employed to estimate the coefficients of covariates, accumulative rate functions and the proportions of zero-recurrence subjects. The large-sample properties ofthe estimators are established as well. Simulations are performed to evaluate the estimationprocedure and an example of application on a set of migration data is provided to illustrateour proposed models and methods.

Suggested Citation

  • Xiaobing Zhao & Jinglong Wang & Xian Zhou & Zhongyi Zhu, 2015. "Recurrent Events Analysis in the Presence of Terminal Event and Zero-recurrence Subjects," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 44(4), pages 710-725, February.
    • Handle: RePEc:taf:lstaxx:v:44:y:2015:i:4:p:710-725
    DOI: 10.1080/03610926.2012.753085
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    Cited by:

    1. Wang, Weiwei & Wu, Xianyi & Zhao, Xiaobing & Zhou, Xian, 2018. "Robust variable selection of joint frailty model for panel count data," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 60-78.

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