Covariate adjustment for non-parametric tests for censored survival data

We develop a method for covariate adjustment for a general class of non-parametric tests for censored survival data which includes the widely used logrank and Wilcoxon tests. The covariate-adjusted tests improve the power of the unadjusted counterparts and have advantages over the covariate-adjusted Cox score test when there are outliers in the covariable space. We investigate the small sample properties of such test statistics through Monte Carlo simulations. Examples are given to illustrate the proposed procedures. Copyright (C) 2001 John Wiley & Sons, Ltd.