A method for comparing semi-parametric models with parametric models in competing risks analysis.

In survival analysis, Cox's regression model is often used to assess the effect of covariates on the time of failure. This semi-parametric model has been extended to the situation where more than one cause of failure is of interest. In this paper, two semi-parametric models for the analysis of competing risks with covariates in the presence of independent random censoring are considered. Particular attention is devoted to the comparison between the two models. A method using a measure derived from the generalized variance is proposed. This method is illustrated with an example in a cancer clinical trial. A FORTRAN program for the computer implementation of the method is also discussed.