Assessing Group Differences in Estimated Baseline Survivor Functions From Cox Proportional Hazards Models

Abstract

The author discusses the general problem of evaluating differences in adjusted survivor functions and develops a heuristic approach to generate the expected events that would occur under a Cox proportional hazards model. Differences in the resulting expected survivor distributions can be tested using generalized log rank tests. This method should prove useful for making other kinds of comparisons and generating adjusted life tables. The author also discusses alternative specifications of the classical Cox model that allow time-varying effects and thus permit a more direct assessment of group differences at various points in time. He implements recently developed semiparametric approaches for estimating time-varying effects, which permit statistical tests of group difference in effects as well as tests of time-invariant effects. He shows that these approaches can provide insight into the nature of time-varying effects and can help reveal the temporal dynamic of group differences.