A TEST OF FIT FOR A SEMIPARAMETRIC ADDITIVE RISK MODEL

Kolmogorov-Smirnov and Cramer-von Mises type test statistics based on the standardised cumulative hazard process are proposed. It is very di fficult to evaluate their asymptotic distributions, but they can be ap proximated by the use of the bootstrap. The advantages of the goodness -of-fit test are that arbitrary partitions of the time axis and covari ate spaces are not needed for evaluating test statistics and that it h as excellent consistency properties. The test is applied to data from the Mayo Clinic trial in primary biliary cirrhosis of the liver. A sim ulation study indicates that the proposed test is suitable for practic al use.