Journal ArticleDOI
The area above the ordinal dominance graph and the area below the receiver operating characteristic graph
TLDR
In this article, receiver operating characteristic graphs are shown to be a variant form of ordinal dominance graphs, and several different methods of constructing confidence intervals for the area measure are presented and the strengths and weaknesses of each of these methods are discussed.About:
This article is published in Journal of Mathematical Psychology.The article was published on 1975-11-01. It has received 1409 citations till now. The article focuses on the topics: Estimator & U-statistic.read more
Citations
More filters
Journal ArticleDOI
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
TL;DR: 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 and 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 random chosen non-diseased subject.
Journal ArticleDOI
Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.
TL;DR: A nonparametric approach to the analysis of areas under correlated ROC curves is presented, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
Journal ArticleDOI
Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.
Mark H. Zweig,Gregory Campbell +1 more
TL;DR: Receiver-operating characteristic (ROC) plots provide a pure index of accuracy by demonstrating the limits of a test's ability to discriminate between alternative states of health over the complete spectrum of operating conditions.
Journal ArticleDOI
Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond
TL;DR: Two new measures, one based on integrated sensitivity and specificity and the other on reclassification tables, are introduced that offer incremental information over the AUC and are proposed to be considered in addition to the A UC when assessing the performance of newer biomarkers.
Book ChapterDOI
Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors
TL;DR: An easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes.
References
More filters
Book
Signal detection theory and psychophysics
David M. Green,John A. Swets +1 more
TL;DR: This book discusses statistical decision theory and sensory processes in signal detection theory and psychophysics and describes how these processes affect decision-making.
Journal ArticleDOI
On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
Henry B. Mann,D. R. Whitney +1 more
TL;DR: In this paper, the authors show that the limit distribution is normal if n, n$ go to infinity in any arbitrary manner, where n = m = 8 and n = n = 8.
Journal ArticleDOI
Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability
Lucien Le Cam,Neyman Jerzy +1 more
Journal ArticleDOI
Consistency and Unbiasedness of Certain Nonparametric Tests
TL;DR: In this paper, it was shown that there exist strictly unbiased and consistent tests for the univariate and multivariate two-and fc-sample problem, for the hypothesis of independence, and for the hypotheses of symmetry with respect to a given point.
On a Use of the Mann-Whitney Statistic
TL;DR: In this paper, the authors present a survey of the known properties of the U statistic which are of importance for its use in testing hypotheses and discuss another use of this statistic which has attracted less attention.