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Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
Author(s) -
Klein John P.,
Andersen Per Kragh
Publication year - 2005
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2005.031209.x
Subject(s) - cumulative incidence , statistics , jackknife resampling , statistic , estimator , mathematics , proportional hazards model , incidence (geometry) , regression analysis , hazard , regression , econometrics , cumulative risk , weibull distribution , medicine , cohort , geometry , chemistry , organic chemistry
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.