title: Pseudo-observations for competing risks with covariate dependent censoring.
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.
authors: Institute of Medical Biometry and Medical Informatics, University Medical Center Freiburg, Stefan-Meier-Str. 26, 79104 , Freiburg, Germany, nadine@imbi.uni-freiburg.de.
authors: Nadine
authors: N
authors: Binder
authors: Thomas A
authors: TA
authors: Gerds
authors: Per Kragh
authors: PK
authors: Andersen
mesh_terms: D015982:Bias; D016026:Bone Marrow Transplantation; D003198:Computer Simulation; D006801:Humans; D007938:Leukemia / Q000628:therapy; D015993:Life Tables; D015233:Models, Statistical; D012008:Recurrence; D012044:Regression Analysis; D012306:Risk; D016019:Survival Analysis