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Nonparametric inference for panel count data with competing risks

Author

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  • E. P. Sreedevi
  • P. G. Sankaran

Abstract

In survival and reliability studies, panel count data arise when we investigate a recurrent event process and each study subject is observed only at discrete time points. If recurrent events of several types are possible, we obtain panel count data with competing risks. Such data arise frequently from transversal studies on recurrent events in demography, epidemiology and reliability experiments where the individuals cannot be observed continuously. In the present paper, we propose an isotonic regression estimator for the cause specific mean function of the underlying recurrent event process of a competing risks panel count data. Further, a nonparametric test is proposed to compare the cause specific mean functions of the panel count competing risks data. Asymptotic properties of the proposed estimator and test statistic are studied. A simulation study is conducted to assess the finite sample behaviour of the proposed estimator and test statistic. Finally, the procedures developed are applied to a real data arising from skin cancer chemo prevention trial.

Suggested Citation

  • E. P. Sreedevi & P. G. Sankaran, 2021. "Nonparametric inference for panel count data with competing risks," Journal of Applied Statistics, Taylor & Francis Journals, vol. 48(16), pages 3102-3115, December.
    • Handle: RePEc:taf:japsta:v:48:y:2021:i:16:p:3102-3115
    DOI: 10.1080/02664763.2020.1795816
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