Nonparametric analysis of an accelerated failure time model

Abstract

SUMMARY Survival distributions can be characterized by and compared through their hazard functions. Tests using a proportional hazards model have good power if the two hazards do not cross, but without time-dependant covariates can have low power if they do. The method contained herein is designed to provide a complement to the proportional hazards model. Differences in survival distributions are parameterized by a scale change and the log rank statistic is used to generate an estimate of the change and a confidence interval based test. This approach is fully efficient for the Weibull family with no censoring. In general it compares favourably with the proportional hazards approach, although neither method dominates.