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Statistica Sinica 33 (2023), 983-1001

THE IDENTIFIABILITY OF COPULA MODELS FOR
DEPENDENT COMPETING RISKS DATA WITH
EXPONENTIALLY DISTRIBUTED MARGINS

Antai Wang

New Jersey Institute of Technology

Abstract: We prove the identifiability property of Archimedean copula models for dependent competing risks data when at least one of the failure times is exponentially distributed. With this property, it becomes possible to quantify the dependence between competing events based on exponentially distributed dependent censored data. We demonstrate our estimation procedure using simulation studies and in an application to survival data.

Key words and phrases: Archimedean copula models, copula graphic estimator, identifiability of competing risks data.

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