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Biometrika Advance Access published online on February 4, 2008
Biometrika, doi:10.1093/biomet/asm096
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© 2008 Biometrika Trust

Articles

Predicting cumulative incidence probability by direct binomial regression

Thomas H. Scheike

Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, 1014 Copenhagen, Denmark ts{at}pubhealth.ku.dk

Mei-Jie Zhang

Division of Biostatistics, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, Wisconsin 53226, U.S.A. meijie{at}mcw.edu

Thomas A. Gerds

Institute of Medical Biometry and Medical Informatics, University of Freiburg, Stefan-Meier-Strasse 26, 79104 Freiburg, Germany gerds{at}fdm.uni-freiburg.de

Received for publication 1 March 2004. Revision received 1 July 2007.
  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.

Key Words: Binomial modelling • Cause-specific hazard • Cumulative incidence probability • Subdistribution hazard


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