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Conditional modeling of recurrent event data with terminal event

Author

Listed:
  • Weiyu Fang

    (Capital Normal University)

  • Jie Zhou

    (Capital Normal University)

  • Mengqi Xie

    (Capital Normal University)

Abstract

Recurrent event data with a terminal event arise in follow-up studies. The current literature has primarily focused on the effect of covariates on the recurrent event process using marginal estimating equation approaches or joint modeling approaches via frailties. In this article, we propose a conditional model for recurrent event data with a terminal event, which provides an intuitive interpretation of the effect of the terminal event: at an early time, the rate of recurrent events is nearly independent of the terminal event, but the dependence gets stronger as time goes close to the terminal event time. A two-stage likelihood-based approach is proposed to estimate parameters of interest. Asymptotic properties of the estimators are established. The finite-sample behavior of the proposed method is examined through simulation studies. A real data of colorectal cancer is analyzed by the proposed method for illustration.

Suggested Citation

  • Weiyu Fang & Jie Zhou & Mengqi Xie, 2025. "Conditional modeling of recurrent event data with terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 31(1), pages 187-204, January.
    • Handle: RePEc:spr:lifeda:v:31:y:2025:i:1:d:10.1007_s10985-024-09637-8
    DOI: 10.1007/s10985-024-09637-8
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