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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Pseudo-observations for competing risks with covariate dependent censoring
Nadine Binder1, Thomas A Gerds, Per Kragh Andersen
1Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Stefan-Meier-Str. 26, 79104 , Freiburg, Germany, nadine@imbi.uni-freiburg.de.
Abstract:
Regression analysis for competing risks data can be based on generalized estimating equations. For the case with right censored data, pseudo-values were proposed to solve the estimating equations. In this article we investigate robustness of the pseudo-values against violation of the assumption that the probability of not being lost to follow-up (un-censored) is independent of the covariates. Modified pseudo-values are proposed which rely on a correctly specified regression model for the censoring times. Bias and efficiency of these methods are compared in a simulation study. Further illustration of the differences is obtained in an application to bone marrow transplantation data and a corresponding sensitivity analysis.
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