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Simex approaches to measurement error in roc studies
Authors:Jonghyeon Kim  Leon J. Gleser
Affiliation:Department of Statistics , University of Pittsburgh , Pittsburgh, PA, 15260, U.S.A.
Abstract:This paper explores the estimation of the area under the ROC curve when test scores are subject to errors. The naive approach that ignores measurement errors generally yields inconsistent estimates. Finding the asymptotic bias of the naive estimator, Coffin and Sukhatme (1995, 1997) proposed bias-corrected estimators for parametric and nonparametric cases. However, the asymptotic distributions of these estimators have not been developed because of their complexity. We propose several alternative approaches, including the SIMEX procedure of Cook and Stefanski (1994). We also provide the asymptotic distributions of the SIMEX estimators for use in statistical inference. Small simulation studies illustrate that the SIMEX estimators perform reasonably well when compared to the bias-corrected estimators.
Keywords:ROC curve  Bias connection  Regression calibration  Empirical Bayes  UMVUE  Simulation and Extrapolation
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