2004•Unpublished venueRequires access

A study on the conditional survival function with random censored data

Won-Kee Lee, Myung-Unn Song

Abstract

In the analysis of cancer data, it is important to make inferences of survival function and to assess the effects of covariates. Cox's proportional hazard model(PHM) and Beran's nonparametric method are generally used to estimate the survival function with covariates. We adjusted the incomplete survival time using the Buckley and James's(1979) pseudo random variables, and then proposed the estimator for the conditional survival function. Also, we carried out the simulation studies to compare the performances of the proposed method.

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Available abstract

Key concepts: Covariate, Survival function, Proportional hazards model, Statistics, Estimator, Survival analysis, Econometrics, Nonparametric statistics