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Generalized Accelerated Failure Time Models for Recurrent Events

Author

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  • Xiaoyi Wen

    (The Institute of Statistics and Big Data, Renmin University of China, Beijing 100872, China)

  • Jinfeng Xu

    (School of Mathematics, Yunnan Normal University, Kunming 650092, China)

Abstract

For analyzing recurrent event data, we consider a generalization of the classical accelerated failure time model. In the proposed approach, the general function is no longer assumed to be a singleton but allowed to be time-varying. This is in the same spirit as in quantile regression and the counting process techniques can be utilized. Theoretical properties such as consistency and asymptotic normality are obtained. The illustration of the methodology using simulation studies and then the application to the bladder cancer data is also given.

Suggested Citation

  • Xiaoyi Wen & Jinfeng Xu, 2022. "Generalized Accelerated Failure Time Models for Recurrent Events," Mathematics, MDPI, vol. 10(15), pages 1-14, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:15:p:2662-:d:874560
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    References listed on IDEAS

    as
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