Identifiability and Estimation of Marginal Survival Functions for Dependent Competing Risks Assuming the Copula is Known

  • Ming Zheng
  • John P. Klein


We show that if the copula between the two marginal distributions is known then the competing risks data is sufficient to identify the marginal survival function. An estimator is constructed to estimate the marginal survival functions based on an assumed copula. This estimator is shown to be consistent and to reduce to the Kaplan-Meier estimator when the death and censoring times are independent. Results of a simulation study are presented to compare this estimator to other estimators.


Marginal Distribution Archimedean Copula Marginal Distribution Function Censoring Time Nonparametric Maximum Likelihood Estimator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 1996

Authors and Affiliations

  • Ming Zheng
    • 1
    • 2
  • John P. Klein
    • 1
    • 2
  1. 1.Department of StatisticsThe Ohio State UniversityColumbusUSA
  2. 2.Division of BiostatisticsThe Medical College of WisconsinMilwaukeeUSA

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