Journal ArticleDOI
Estimation of the area under the ROC curve.
David Faraggi,Benjamin Reiser +1 more
TLDR
This paper discusses and compares estimation procedures for the area under the receiver operating characteristic curve based on the Mann-Whitney statistic; kernel smoothing; normal assumptions; empirical transformations to normality; and compares these in terms of bias and root mean square error.Abstract:
The area under the receiver operating characteristic curve is frequently used as a measure for the effectiveness of diagnostic markers. In this paper we discuss and compare estimation procedures for this area. These are based on (i) the Mann-Whitney statistic; (ii) kernel smoothing; (iii) normal assumptions; (iv) empirical transformations to normality. These are compared in terms of bias and root mean square error in a large variety of situations by means of an extensive simulation study. Overall we find that transforming to normality usually is to be preferred except for bimodal cases where kernel methods can be effective.read more
Citations
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Journal ArticleDOI
Estimation of the Youden Index and its associated cutoff point.
TL;DR: This paper compares several estimation procedures for the Youden Index and its associated cutoff point and finds that the empirical method which is the most commonly used has the overall worst performance.
Journal Article
Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation
TL;DR: This review provides the basic principle and rational for ROC analysis of rating and continuous diagnostic test results versus a gold standard and the methods of estimate and testing of AUC and its testing in single diagnostic test and also comparative studies.
Journal ArticleDOI
The use of receiver operating characteristic curves in biomedical informatics
TL;DR: The basic concepts of ROC analysis are reviewed, their use with sample calculations, make recommendations drawn from the literature, and list readily available software are made.
Journal ArticleDOI
Receiver operating characteristic (ROC) curve for medical researchers
Rajeev Kumar,Abhaya Indrayan +1 more
TL;DR: The aim of this article is to provide basic conceptual framework and interpretation of ROC analysis to help medical researchers to use it effectively.
Journal ArticleDOI
Understanding receiver operating characteristic (ROC) curves
TL;DR: It is concluded that serum levels of neuron-specific enolase (NSE), a biochemical marker of ischemic brain injury, may have clinical utility for the prediction of survival to hospital discharge in patients experiencing the return of spontaneous circulation following at least 5 minutes of cardiopulmonary resuscitation.
References
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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
An Analysis of Transformations
George E. P. Box,David Cox +1 more
TL;DR: In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.
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
The area above the ordinal dominance graph and the area below the receiver operating characteristic graph
TL;DR: 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.
Journal ArticleDOI
Some practical issues of experimental design and data analysis in radiological ROC studies.
TL;DR: The purposes of this paper are to make users of ROC methodology in medical imaging aware of potential problems that should be confronted before an ROC study is begun and to indicate, at least broadly, how those problems may be dealt with, given the present state of the art.