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A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events

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  • Xiaowei Sun

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jieli Ding

    (Wuhan University)

  • Liuquan Sun

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

Recurrent event data with a terminal event commonly arise in longitudinal follow-up studies. We use a weighted composite endpoint of all recurrent and terminal events to assess the overall effects of covariates on the two types of events. A semiparametric additive rates model is proposed to analyze the weighted composite event process and the dependence structure among recurrent and terminal events is left unspecified. An estimating equation approach is developed for inference, and the asymptotic properties of the resulting estimators are established. The finite-sample behavior of the proposed estimators is evaluated through simulation studies, and an application to a bladder cancer study is illustrated.

Suggested Citation

  • Xiaowei Sun & Jieli Ding & Liuquan Sun, 2020. "A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 471-492, July.
    • Handle: RePEc:spr:lifeda:v:26:y:2020:i:3:d:10.1007_s10985-019-09486-w
    DOI: 10.1007/s10985-019-09486-w
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    References listed on IDEAS

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    1. Xingqiu Zhao & Jie Zhou & Liuquan Sun, 2011. "Semiparametric Transformation Models with Time-Varying Coefficients for Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 67(2), pages 404-414, June.
    2. Gongjun Xu & Sy Han Chiou & Chiung-Yu Huang & Mei-Cheng Wang & Jun Yan, 2017. "Joint Scale-Change Models for Recurrent Events and Failure Time," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 794-805, April.
    3. Donglin Zeng & D. Y. Lin, 2009. "Semiparametric Transformation Models with Random Effects for Joint Analysis of Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 65(3), pages 746-752, September.
    4. Yining Ye & John D. Kalbfleisch & Douglas E. Schaubel, 2007. "Semiparametric Analysis of Correlated Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 63(1), pages 78-87, March.
    5. Debashis Ghosh & D. Y. Lin, 2000. "Nonparametric Analysis of Recurrent Events and Death," Biometrics, The International Biometric Society, vol. 56(2), pages 554-562, June.
    6. Chiung-Yu Huang & Mei-Cheng Wang, 2004. "Joint Modeling and Estimation for Recurrent Event Processes and Failure Time Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1153-1165, December.
    7. Lei Liu & Robert A. Wolfe & Xuelin Huang, 2004. "Shared Frailty Models for Recurrent Events and a Terminal Event," Biometrics, The International Biometric Society, vol. 60(3), pages 747-756, September.
    8. 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.
    9. John D. Kalbfleisch & Douglas E. Schaubel & Yining Ye & Qi Gong, 2013. "An Estimating Function Approach to the Analysis of Recurrent and Terminal Events," Biometrics, The International Biometric Society, vol. 69(2), pages 366-374, June.
    10. Bedair, Khaled & Hong, Yili & Li, Jie & Al-Khalidi, Hussein R., 2016. "Multivariate frailty models for multi-type recurrent event data and its application to cancer prevention trial," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 161-173.
    11. Donglin Zeng & Jianwen Cai, 2010. "A semiparametric additive rate model for recurrent events with an informative terminal event," Biometrika, Biometrika Trust, vol. 97(3), pages 699-712.
    12. Huijuan Ma & Limin Peng & Zhumin Zhang & HuiChuan J. Lai, 2018. "Generalized accelerated recurrence time model for multivariate recurrent event data with missing event type," Biometrics, The International Biometric Society, vol. 74(3), pages 954-965, September.
    13. Wang M-C. & Qin J. & Chiang C-T., 2001. "Analyzing Recurrent Event Data With Informative Censoring," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1057-1065, September.
    14. Zeng, Donglin & Lin, D.Y., 2007. "Semiparametric Transformation Models With Random Effects for Recurrent Events," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 167-180, March.
    15. Hsiang Yu & Yu‐Jen Cheng & Ching‐Yun Wang, 2018. "Methods for multivariate recurrent event data with measurement error and informative censoring," Biometrics, The International Biometric Society, vol. 74(3), pages 966-976, September.
    16. Cook, Richard J. & Lawless, Jerald F. & Lakhal-Chaieb, Lajmi & Lee, Ker-Ai, 2009. "Robust Estimation of Mean Functions and Treatment Effects for Recurrent Events Under Event-Dependent Censoring and Termination: Application to Skeletal Complications in Cancer Metastatic to Bone," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 60-75.
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