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 in | Biometrical journal Vol. 41; no. 1; pp. 25 - 31 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Berlin
WILEY-VCH Verlag Berlin GmbH
01.03.1999
WILEY‐VCH Verlag Berlin GmbH Wiley-VCH |
Subjects | |
Online Access | Get full text |
ISSN | 0323-3847 1521-4036 |
DOI | 10.1002/(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. |
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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. |
Author_xml | – sequence: 1 givenname: Robert A. surname: Parker fullname: Parker, Robert A. email: robert_parker@bidmc.harvard.edu organization: Beth Israel-Deaconess Medical Center and Harvard Medical School, Boston, USA – sequence: 2 givenname: Roger B. surname: Davis fullname: Davis, Roger B. organization: Beth Israel-Deaconess Medical Center and Harvard Medical School, Boston, USA |
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Copyright | 1999 WILEY‐VCH Verlag Berlin GmbH, Fed. Rep. of Germany 1999 INIST-CNRS |
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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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