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Non-parametric test of recurrent cumulative incidence functions for competing risks models

Author

Listed:
  • M. S. Sisuma

    (Cochin University of Science and Technology)

  • P. G. Sankaran

    (Cochin University of Science and Technology)

Abstract

Recurrent competing risks data are common in survival studies. In such contexts the effects of competing risks on lifetime outcomes are important problem of study. In this work we introduce recurrent cumulative incidence function and then propose a non-parametric test for comparing recurrent cumulative incidence functions. Asymptotic distribution of the test statistic is derived. A simulation study is carried out to assess the performance of the proposed test statistic. The proposed method is applied to an auto-mobile warranty data.

Suggested Citation

  • M. S. Sisuma & P. G. Sankaran, 2022. "Non-parametric test of recurrent cumulative incidence functions for competing risks models," METRON, Springer;Sapienza Università di Roma, vol. 80(3), pages 331-342, December.
    • Handle: RePEc:spr:metron:v:80:y:2022:i:3:d:10.1007_s40300-022-00228-x
    DOI: 10.1007/s40300-022-00228-x
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    References listed on IDEAS

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    1. Anupap Somboonsavatdee & Ananda Sen, 2015. "Parametric inference for multiple repairable systems under dependent competing risks," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(5), pages 706-720, September.
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    3. Natalia A. Gouskova & Feng-Chang Lin & Jason P. Fine, 2017. "Nonparametric analysis of competing risks data with event category missing at random," Biometrics, The International Biometric Society, vol. 73(1), pages 104-113, March.
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    5. P. G. Sankaran & P. Anisha, 2011. "Shared frailty model for recurrent event data with multiple causes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2859-2868, February.
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