Recommended methods to compare the accuracy of two binary diagnostic tests subject to a paired design

This manuscript assesses different methods to compare the sensitivities and the specificities of two diagnostic tests. It studies the comparison conditioning on the disease status and testing each hypothesis test individually to an error , a global hypothesis test to simultaneously compare the param...

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Published inJournal of statistical computation and simulation Vol. 89; no. 14; pp. 2621 - 2644
Main Authors Roldán-Nofuentes, J. A., Sidaty-Regad, S. B.
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 22.09.2019
Taylor & Francis Ltd
Subjects
6207
Binary diagnostic test
Diagnostic systems
Diagnostic tests
global hypothesis test
Hypotheses
Parameters
sensitivity
Sensitivity analysis
specificity
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ISSN0094-9655
1563-5163
DOI10.1080/00949655.2019.1628234

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Abstract This manuscript assesses different methods to compare the sensitivities and the specificities of two diagnostic tests. It studies the comparison conditioning on the disease status and testing each hypothesis test individually to an error , a global hypothesis test to simultaneously compare the parameters, and the individual comparison of the parameters along with the multiple comparison methods of Bonferroni and Holm. Simulation experiments were carried out to study the global type I errors and the global powers of the different methods, providing some general rules of application. When the prevalence is small and the sample size is small or moderate, it is recommended to compare the parameters individually along with the method of Bonferroni or Holm; in any other situation, it is recommended to compare the parameters simultaneously through a global test. The results were applied to an example of the diagnosis of coronary disease.
AbstractList This manuscript assesses different methods to compare the sensitivities and the specificities of two diagnostic tests. It studies the comparison conditioning on the disease status and testing each hypothesis test individually to an error [Formula omitted.] , a global hypothesis test to simultaneously compare the parameters, and the individual comparison of the parameters along with the multiple comparison methods of Bonferroni and Holm. Simulation experiments were carried out to study the global type I errors and the global powers of the different methods, providing some general rules of application. When the prevalence is small and the sample size is small or moderate, it is recommended to compare the parameters individually along with the method of Bonferroni or Holm; in any other situation, it is recommended to compare the parameters simultaneously through a global test. The results were applied to an example of the diagnosis of coronary disease.
This manuscript assesses different methods to compare the sensitivities and the specificities of two diagnostic tests. It studies the comparison conditioning on the disease status and testing each hypothesis test individually to an error , a global hypothesis test to simultaneously compare the parameters, and the individual comparison of the parameters along with the multiple comparison methods of Bonferroni and Holm. Simulation experiments were carried out to study the global type I errors and the global powers of the different methods, providing some general rules of application. When the prevalence is small and the sample size is small or moderate, it is recommended to compare the parameters individually along with the method of Bonferroni or Holm; in any other situation, it is recommended to compare the parameters simultaneously through a global test. The results were applied to an example of the diagnosis of coronary disease.
Author Roldán-Nofuentes, J. A.
Sidaty-Regad, S. B.
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Binary diagnostic test
Diagnostic systems
Diagnostic tests
global hypothesis test
Hypotheses
Parameters
sensitivity
Sensitivity analysis
specificity
Title Recommended methods to compare the accuracy of two binary diagnostic tests subject to a paired design
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