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Comparing sub-survival functions in a competing risks model
1Department of Mathematical Sciences, University of Alberta, Edmonton. kc.carriere@ualberta.ca
Abstract:
In the competing risks literature, one usually compares whether two risks are equal or whether one is "more serious." In this paper, we propose tests for the equality of two competing risks against an ordered alternative specified by their sub-survival functions. These tests are naturally developed as extensions of those based on hazard rates and cumulative incidence functions. We note that the interpretation of the new test results is more direct compared to the situation when the hypotheses are framed in terms of their cumulative incidence functions. The proposed tests are of the Kolmogrov-Smirnov type, based on maximum differences between sub-survival functions. Our simulation studies indicate that they are excellent competitors of the existing tests, that are based mainly on differences between cumulative incidence functions. A numerical example will demonstrate the advantages of the proposed tests.