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      Is Carotid Intima-Media Thickness Useful in Cardiovascular Disease Risk Assessment? : The Rotterdam Study

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          Most cited references 18

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          The meaning and use of the area under a receiver operating characteristic (ROC) curve.

          A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
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            A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

            Receiver operating characteristic (ROC) curves are used to describe and compare the performance of diagnostic technology and diagnostic algorithms. This paper refines the statistical comparison of the areas under two ROC curves derived from the same set of patients by taking into account the correlation between the areas that is induced by the paired nature of the data. The correspondence between the area under an ROC curve and the Wilcoxon statistic is used and underlying Gaussian distributions (binormal) are assumed to provide a table that converts the observed correlations in paired ratings of images into a correlation between the two ROC areas. This between-area correlation can be used to reduce the standard error (uncertainty) about the observed difference in areas. This correction for pairing, analogous to that used in the paired t-test, can produce a considerable increase in the statistical sensitivity (power) of the comparison. For studies involving multiple readers, this method provides a measure of a component of the sampling variation that is otherwise difficult to obtain.
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              Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach

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                Author and article information

                Journal
                Stroke
                Stroke
                Ovid Technologies (Wolters Kluwer Health)
                0039-2499
                1524-4628
                July 2001
                July 2001
                : 32
                : 7
                : 1532-1538
                Affiliations
                [1 ]From the Department of Epidemiology and Biostatistics, Erasmus Medical Center, Rotterdam (A.I. del S., M.H., A.H., D.E.G., M.M.B.B., J.C.M.W., M.L.B.); Julius Center for Patient Oriented Research, University Medical Center Utrecht (A.I. del S., K.G.M.M., D.E.G., M.L.B.); and Department of Neurology, University Hospital Rotterdam (P.J.K.) (Netherlands).
                Article
                10.1161/01.STR.32.7.1532
                © 2001

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