The graphical evaluation of explanatory variables in proportional hazard regression models

Abstract

A graphical technique for assessing explanatory variables in Cox's proportional hazards regression model is examined. The method arises from consideration of the cumulative hazard transformation and the partial likelihood score function, and consists of permuting the observed rank statistic to account for the effects of explanatory variables fitted to the model. An example is provided.