Survival Analysis Using a Censored Semiparametric Regression Model

In this work we study the effect of several covariates X on a censored response variable T with unknown probability distribution. A semiparametric model is proposed to consider situations where the functional form of the effect of one or more covariates is unknown. We provide its estimation procedure and, in addition, a bootstrap technique to make inference on the parameters. An application with a real dataset is presented, as well as some simulation results, to demonstrate the good behavior of the proposed estimation process and to analyze the effect of the censorship. This new model has an important application field in reliability, survival or lifetime data analysis.