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A comparison of denominator degrees of freedom methods for multiple observer ROC analysis

A comparison of denominator degrees of freedom methods for multiple observer ROC analysis There are several methods available for analysing multireader ROC studies that generalize results to both the reader and case populations. Two of these methods—the Dorfman–Berbaum–Metz (DBM) method and the Obuchowki–Rockette (OR) method—appear to be quite different in their original formulations. However, recently it has been shown that the DBM and OR procedures yield the same test statistic when based on the same accuracy measure and covariance estimation method, but inferences can vary depending on which denominator degrees of freedom (ddf) method, DBM or OR, is used. I show in simulations that there are problems with both ddf methods: OR is ultraconservative with significance levels considerably below the nominal level, and DBM can result in extremely wide confidence intervals because the ddf can be close to zero. I propose a new ddf method that overcomes both of these problems and can be used with either the OR or DBM procedure. Copyright © 2006 John Wiley & Sons, Ltd. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Statistics in Medicine Wiley

A comparison of denominator degrees of freedom methods for multiple observer ROC analysis

Statistics in Medicine , Volume 26 (3) – Jan 10, 2007

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References (37)

Publisher
Wiley
Copyright
Copyright © 2007 Wiley Subscription Services
ISSN
0277-6715
eISSN
1097-0258
DOI
10.1002/sim.2532
pmid
16538699
Publisher site
See Article on Publisher Site

Abstract

There are several methods available for analysing multireader ROC studies that generalize results to both the reader and case populations. Two of these methods—the Dorfman–Berbaum–Metz (DBM) method and the Obuchowki–Rockette (OR) method—appear to be quite different in their original formulations. However, recently it has been shown that the DBM and OR procedures yield the same test statistic when based on the same accuracy measure and covariance estimation method, but inferences can vary depending on which denominator degrees of freedom (ddf) method, DBM or OR, is used. I show in simulations that there are problems with both ddf methods: OR is ultraconservative with significance levels considerably below the nominal level, and DBM can result in extremely wide confidence intervals because the ddf can be close to zero. I propose a new ddf method that overcomes both of these problems and can be used with either the OR or DBM procedure. Copyright © 2006 John Wiley & Sons, Ltd.

Journal

Statistics in MedicineWiley

Published: Jan 10, 2007

Keywords: ; ; ;

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