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Predicting cumulative incidence probability by direct binomial regression

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  • Thomas H. Scheike
  • Mei-Jie Zhang
  • Thomas A. Gerds

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.

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  • Thomas H. Scheike & Mei-Jie Zhang & Thomas A. Gerds, 2008. "Predicting cumulative incidence probability by direct binomial regression," Biometrika, Biometrika Trust, vol. 95(1), pages 205-220.
    • Handle: RePEc:oup:biomet:v:95:y:2008:i:1:p:205-220
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    File URL: http://hdl.handle.net/10.1093/biomet/asm096
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