Evaluating Whether a Binary Decision Rule Operates Better Than Chance

We provide an approach to testing whether the accuracy of a binary diagnostic test, which we define as the sum of sensitivity and specificity, is significantly better than chance. We derive an exact confidence interval of size at least 1 — α for the observed accuracy of the test. In addition, we dev...

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Published inBiometrical journal Vol. 41; no. 1; pp. 25 - 31
Main Authors Parker, Robert A., Davis, Roger B.
Format Journal Article
LanguageEnglish
Published Berlin WILEY-VCH Verlag Berlin GmbH 01.03.1999
WILEY‐VCH Verlag Berlin GmbH
Wiley-VCH
Subjects
Online AccessGet full text
ISSN0323-3847
1521-4036
DOI10.1002/(SICI)1521-4036(199903)41:1<25::AID-BIMJ25>3.0.CO;2-A

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Abstract We provide an approach to testing whether the accuracy of a binary diagnostic test, which we define as the sum of sensitivity and specificity, is significantly better than chance. We derive an exact confidence interval of size at least 1 — α for the observed accuracy of the test. In addition, we develop tests to compare the accuracy of two such tests applied to the same subjects. These results offer a method for assessing the accuracy of a test at a single test criterion, in contrast to the standard approach of evaluating the total receiver‐operating characteristic (ROC) curve for a test.
AbstractList We provide an approach to testing whether the accuracy of a binary diagnostic test, which we define as the sum of sensitivity and specificity, is significantly better than chance. We derive an exact confidence interval of size at least 1 — α for the observed accuracy of the test. In addition, we develop tests to compare the accuracy of two such tests applied to the same subjects. These results offer a method for assessing the accuracy of a test at a single test criterion, in contrast to the standard approach of evaluating the total receiver‐operating characteristic (ROC) curve for a test.
We provide an approach to testing whether the accuracy of a binary diagnostic test, which we define as the sum of sensitivity and specificity, is significantly better than chance. We derive an exact confidence interval of size at least 1 - for the observed accuracy of the test. In addition, we develop tests to compare the accuracy of two such tests applied to the same subjects. These results offer a method for assessing the accuracy of a test at a single test criterion, in contrast to the standard approach of evaluating the total receiver-operating characteristic (ROC) curve for a test.
Author Parker, Robert A.
Davis, Roger B.
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Issue 1
Keywords Receiver operating characteristic curves
Binary decision diagram
Confidence interval
Decision rule
Language English
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Snippet We provide an approach to testing whether the accuracy of a binary diagnostic test, which we define as the sum of sensitivity and specificity, is significantly...
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SubjectTerms Exact sciences and technology
Linear inference, regression
Mathematics
Nonparametric inference
Probability and statistics
Receiver-operating characteristic curve
ROC
Sciences and techniques of general use
Sensitivity
Specificity
Statistics
Youden's misclassification index
Title Evaluating Whether a Binary Decision Rule Operates Better Than Chance
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