  This paper introduces new effect parameters for factorial survival designs
with possibly right-censored time-to-event data. In the special case of a
two-sample design it coincides with the concordance or Wilcoxon parameter in
survival analysis. More generally, the new parameters describe treatment or
interaction effects and we develop estimates and tests to infer their presence.
We rigorously study the asymptotic properties by means of empirical process
techniques and additionally suggest wild bootstrapping for a consistent and
distribution-free application of the inference procedures. The small sample
performance is discussed based on simulation results. The practical usefulness
of the developed methodology is exemplified on a data example about patients
with colon cancer by conducting one- and two-factorial analyses.
