title: Estimation of the average survival function using a censored data regression model.
abstract: In the presence of covariates information, assuming the linear relationship between a transformation of survival time and covariates, we propose a new estimator of survival function and show its consistency. In addition, a comparison of the proposed estimator with the product-limit estimator introduced by Kaplan and Meier (1958) is performed through Monte Carlo simulation studies. We illustrate the proposed estimator with the updated Stanford heart transplant data.
authors.affiliation: Department of Applied Statistics, University of Suwon, Kyonggido, South Korea.
authors.forename: J
authors.initials: J
authors.lastname: Kim
authors.forename: J
authors.initials: J
authors.lastname: Kim
mesh_terms: D001699:Biometry; D016027:Heart Transplantation / Q000401:mortality; D006801:Humans; D016014:Linear Models; D009010:Monte Carlo Method; D016019:Survival Analysis