Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
Article first published online: 28 FEB 2005
Volume 61, Issue 1, pages 223–229, March 2005
How to Cite
Klein, J. P. and Andersen, P. K. (2005), Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function. Biometrics, 61: 223–229. doi: 10.1111/j.0006-341X.2005.031209.x
- Issue published online: 28 FEB 2005
- Article first published online: 28 FEB 2005
- Received December 2003. Revised June 2004. Accepted June 2004.
- Bone marrow transplantation;
- Generalized estimating equations;
- Jackknife statistics;
- Regression models
Summary Typically, regression models for competing risks outcomes are based on proportional hazards models for the crude hazard rates. These estimates often do not agree with impressions drawn from plots of cumulative incidence functions for each level of a risk factor. We present a technique which models the cumulative incidence functions directly. The method is based on the pseudovalues from a jackknife statistic constructed from the cumulative incidence curve. These pseudovalues are used in a generalized estimating equation to obtain estimates of model parameters. We study the properties of this estimator and apply the technique to a study of the effect of alternative donors on relapse for patients given a bone marrow transplant for leukemia.