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Non-parametric estimation of lifetime distribution of competing risk models when censoring times are missing

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Abstract

There are situations in the analysis of failure time or lifetime data where the censoring times of unfailed units are missing. The non-parametric estimator of the lifetime distribution for such data is available in literature. In this paper we consider an extension of this situation to the univariate and bivariate competing risk setups. The maximum likelihood and simple moment estimators of cause specific distribution functions in both univariate and bivariate situations are developed. A simulation study is carried out to assess the performance of the estimators. Finally, we illustrate the method with real data set.

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Authors and Affiliations

  1. Department of Statistics, Cochin University of Science and Technology, Cochin, 682 022, Kerala, India

    P. G. Sankaran & Ansa Alphonsa Antony

Authors
  1. P. G. Sankaran
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  2. Ansa Alphonsa Antony
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Correspondence to P. G. Sankaran.

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Sankaran, P.G., Antony, A.A. Non-parametric estimation of lifetime distribution of competing risk models when censoring times are missing. Stat Papers 50, 339–361 (2009). https://doi.org/10.1007/s00362-007-0086-z

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  • DOI: https://doi.org/10.1007/s00362-007-0086-z

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