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A varying-coefficient model for gap times between recurrent events

Author

Listed:
  • J. E. Soh

    (Emory University)

  • Yijian Huang

    (Emory University)

Abstract

Recurrent events often arise in follow-up studies where a subject may experience multiple occurrences of the same type of event. Most regression models for recurrent events consider the time scale measured from the study origin and assume constant effects of covariates. In many applications, however, gap times between recurrent events are of natural interest and moreover the effects may actually vary over time. In this article, we propose a marginal varying-coefficient model for gap times between recurrent events that allows for the intra-individual correlation between events. Estimation and inference procedures are developed for the varying coefficients. Consistency and weak convergence of the proposed estimator are established. Monte Carlo simulation studies demonstrate that the proposed method works well with practical sample sizes. The proposed method is illustrated with an analysis of bladder tumor clinical data.

Suggested Citation

  • J. E. Soh & Yijian Huang, 2021. "A varying-coefficient model for gap times between recurrent events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 27(3), pages 437-459, July.
    • Handle: RePEc:spr:lifeda:v:27:y:2021:i:3:d:10.1007_s10985-021-09523-7
    DOI: 10.1007/s10985-021-09523-7
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    References listed on IDEAS

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    1. Yijian Huang, 2014. "Bootstrap for the case-cohort design," Biometrika, Biometrika Trust, vol. 101(2), pages 465-476.
    2. Chin-Tsang Chiang & Mei-Cheng Wang, 2009. "Varying-coefficient model for the occurrence rate function of recurrent events," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(1), pages 197-213, March.
    3. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    4. Peng, Limin & Huang, Yijian, 2008. "Survival Analysis With Quantile Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 637-649, June.
    5. J. P. Fine, 2004. "Temporal process regression," Biometrika, Biometrika Trust, vol. 91(3), pages 683-703, September.
    6. Jing Qian & Limin Peng, 2010. "Censored quantile regression with partially functional effects," Biometrika, Biometrika Trust, vol. 97(4), pages 839-850.
    7. Limin Peng & Yijian Huang, 2007. "Survival analysis with temporal covariate effects," Biometrika, Biometrika Trust, vol. 94(3), pages 719-733.
    8. Yijian Huang, 2017. "Restoration of Monotonicity Respecting in Dynamic Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 613-622, April.
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