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Consistency of the Kaplan-Meier Estimator of the Survival Function in Competiting Risks

Author

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  • Didier Alain Njamen Njomen

    (Department of Mathematics and Computer Sciences, Faculty of Science, University of Maroua, Maroua, Cameroon)

  • Joseph Wandji Ngatchou

    (Institut Elie Cartan de Lorraine, University of Lorraine, Nancy, France)

Abstract

Introduction : In this article, we only focus on the probability distributions of the breakdown time whose causes are known, and we consider a partition of the observations into subgroups according to each of the causes as defined in Njamen and Ngatchou [1]. By adapting the stochastic processes developed by Aalen [2, 3], we derive a Kaplan-Meier [4] nonparametric estimator for the survival function in competiting risks. Result & Discussion : In a region where there is at least one observation, we prove on one hand that this new nonparametric estimator is unbiased in competiting risk and on the other hand, using the Lenglart inequality, we establish its uniform consistency in competiting risks.

Suggested Citation

  • Didier Alain Njamen Njomen & Joseph Wandji Ngatchou, 2018. "Consistency of the Kaplan-Meier Estimator of the Survival Function in Competiting Risks," The Open Statistics and Probability Journal, Bentham Open, vol. 9(1), pages 1-17, April.
  • Handle: RePEc:ben:tostpj:v:9:y:2018:i:1:p:1-17
    DOI: 10.2174/1876527001809010001
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    References listed on IDEAS

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    1. R.D. Gill, 1980. "Censoring and Stochastic Integrals," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 34(2), pages 124-124, June.
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