Testing Goodness of Fit for Proportional Hazards Model with Censored Observations

Abstract

A numerical omnibus test of fit for the two-sample proportional hazards model is proposed for randomly censored observations. The test is derived from Cox's partial likelihood and does not need a dummy time-dependent covariate or any partition of the time-axis. Consistency of the test is established. Examples are provided for illustration.