On Using Stratification in the Analysis of Linear Regression Models with Right Censoring

Abstract

We study two modified synthetic data least-squares estimation methods for linear regression models with right censored response variables, unspecified residual distributions and random censoring variables which may not be i.i.d. These methods are the result of an investigation into the use of stratification. We conclude that stratification should be used whether or not the censoring variables are dependent on the covariates. We give the asymptotic results of the estimators and numerical results.