A proportional hazards model for the analysis of doubly censored competing risks data

P. G. Sankaran and E. P. Sreedevi

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 10, 2975-2987

Abstract: Competing risks data are common in medical research in which lifetime of individuals can be classified in terms of causes of failure. In survival or reliability studies, it is common that the patients (objects) are subjected to both left censoring and right censoring, which is refereed as double censoring. The analysis of doubly censored competing risks data in presence of covariates is the objective of this study. We propose a proportional hazards model for the analysis of doubly censored competing risks data, using the hazard rate functions of Gray (1988), while focusing upon one major cause of failure. We derive estimators for regression parameter vector and cumulative baseline cause specific hazard rate function. Asymptotic properties of the estimators are discussed. A simulation study is conducted to assess the finite sample behavior of the proposed estimators. We illustrate the method using a real life doubly censored competing risks data.

Date: 2016
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DOI: 10.1080/03610926.2014.894064

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