Measurement error and confidence intervals for ROC curves.
Measurement error in a continuous test variable may bias estimates of the summary properties of receiver operating characteristics (ROC) curves. Typically, unbiased measurement error will reduce the diagnostic potential of a continuous test variable. This paper explores the effects of possibly heterogenous measurement error on estimated ROC curves for binormal test variables. Corrected estimators for specific points on the curve are derived under the assumption of known or estimated measurement variances for individual test results. These estimators and associated confidence intervals do not depend on normal assumptions for the distribution of the measurement error and are shown to be approximately unbiased for moderate size samples in a simulation study. An application from a study of emerging imaging modalities in breast cancer is used to demonstrate the new techniques.
Tosteson
Tor D
TD
Dartmouth Medical School, Lebanon, NH 03756, USA. tor.tosteson@dartmouth.edu
Buonaccorsi
John P
JP
Demidenko
Eugene
E
Wells
Wendy A
WA
D003198:Computer Simulation; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003955:Diagnostic Tests, Routine / Q000379:methods*; D008954:Models, Biological; D015233:Models, Statistical; D012372:ROC Curve; D015203:Reproducibility of Results; D012107:Research Design; D012680:Sensitivity and Specificity