Sankhya: The Indian Journal of Statistics
Bivariate Competing Risks Models Under Random Left Truncation and Right Censoring
P.G. Sankaran and Ansa Alphonsa Antony, Cochin University of Science and Technology, Cochin, India
SUMMARY. In survival or reliability studies, it is common to have truncated data due to the limited time span of the study or dropouts of the subjects for various reasons. The estimation of survivor function under left truncation was first discussed by Kaplan and Meier by extending the well known productlimit estimator of the survivor function. The focus of this paper is on the nonparametric estimation of the survivor function and the cause-specific subdistribution functions in bivariate competing risks set up, when the observations are subject to random left truncation and right censoring. Various asymptotic properties of the estimators are discussed. A simulation study discussing the empirical behaviour of the estimator is carried out. We illustrate the procedure by a data set.
AMS (2000) subject classification. Primary 62G05; 62P10.
Key words and phrases. Bivariate survivor function, cause specific distribution functions, vector hazard rate, competing risks models, random truncation.