Predicting cumulative incidence probability by direct binomial regression

Thomas H. Scheike, Mei-Jie Zhang and Thomas A. Gerds

Biometrika, 2008, vol. 95, issue 1, 205-220

Abstract: We suggest a new simple approach for estimation and assessment of covariate effects for the cumulative incidence curve in the competing risks model. We consider a semiparametric regression model where some effects may be time-varying and some may be constant over time. Our estimator can be implemented by standard software. Our simulation study shows that the estimator works well and has finite-sample properties comparable with the subdistribution approach. We apply the method to bone marrow transplant data and estimate the cumulative incidence of death in complete remission following a bone marrow transplantation. Here death in complete remission and relapse are two competing events. Copyright 2008, Oxford University Press.

Date: 2008
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