Regression modeling of competing risks data based on pseudovalues of the cumulative incidence function
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Updated: Aug 19, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
John P Klein1, Per Kragh Andersen
1Division of Biostatistics, Medical College of Wisconsin, 9701 Watertown Plank Road, Milwaukee, Wisconsin 53226, USA. klein@mcw.edu
Abstract:
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.
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