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Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
Elizabeth R. DeLong, David M. DeLong and Daniel L. Clarke-Pearson
Vol. 44, No. 3 (Sep., 1988), pp. 837-845
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/2531595
Page Count: 9
You can always find the topics here!Topics: Covariance, Matrices, Albs, Statistics, Population estimates, Estimation methods, Biometrics, Medical diagnostic tests, Statistical discrepancies, Statistical estimation
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Methods of evaluating and comparing the performance of diagnostic tests are of increasing importance as new tests are developed and marketed. When a test is based on an observed variable that lies on a continuous or graded scale, an assessment of the overall value of the test can be made through the use of a receiver operating characteristic (ROC) curve. The curve is constructed by varying the cutpoint used to determine which values of the observed variable will be considered abnormal and then plotting the resulting sensitivities against the corresponding false positive rates. When two or more empirical curves are constructed based on tests performed on the same individuals, statistical analysis on differences between curves must take into account the correlated nature of the data. This paper presents a nonparametric approach to the analysis of areas under correlated ROC curves, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
Biometrics © 1988 International Biometric Society