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Biometrika 1997 84(3):595-608; doi:10.1093/biomet/84.3.595
© 1997 by Biometrika Trust
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A regression modelling framework for receiver operating characteristic curves in medical diagnostic testing

MARGARET SULLIVAN PEPE

Fred Hutchinson Cancer Research Center, Division of Public Health Sciences 1124 Columbia Street MP-665, Seattle, Washington 98104, U.S.A. e-mail: mspepe{at}u.washington.edu

Receiver operating characteristic curves (ROC'S) are used to evaluate diagnostic tests when test results are not binary. They describe the inherent capacity of the test for distinguishing between truly diseased and nondiseased subjects. Although methodology for estimating and for comparing roc's is well developed, to date no general framework exists for evaluating covariate effects on roc's. We formulate a general regression model which allows the effects of covariates on test accuracy to be succinctly summarised. Such covariates might include, for example, characteristics of the patient or test environment, test type or severity of disease. The regression models are shown to arise naturally from some classic models for continuous or ordinal test data. Regression parameters are fitted using an estimating equation approach. The method is illustrated on data from a study of multiformat photographic images used for scintigraphy.

Key Words: Accuracy • Classification • Screening • Sensitivity • Signal detection


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