Journal
STATISTICS IN MEDICINE
Volume 23, Issue 22, Pages 3437-3449Publisher
WILEY
DOI: 10.1002/sim.1917
Keywords
ROC analysis; diagnostic testing; U-statistics; bootstrap; neuropsychological testing
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Funding
- NCI NIH HHS [P30-CA82709] Funding Source: Medline
- NIMH NIH HHS [R03-MH060565, R01-MH64409] Funding Source: Medline
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Receiver operating characteristic (ROC) curves have been useful in two-group classification problems. In three- and multiple-class diagnostic problems, an ROC surface or hyper-surface can be constructed. The volume under these surfaces can be used for inference using bootstrap techniques or U-statistics theory. In this article, ROC surfaces and hyper-surfaces are defined and their behaviour and utility in multi-group classification problems is investigated. The formulation of the problem is equivalent to what has previously been proposed in the general multi-category classification problem but the definition of ROC surfaces here is less complex and addresses directly the narrower problem of ordered categories in the three-class and, by extension, the multi-class problem applied to continuous and ordinal data. Non-parametric manipulation of both continuous and discrete test data and comparison between two diagnostic tests applied to the same subjects are considered. A three-group classification example in the context of HIV neurological disease is presented and the results are discussed. Copyright (C) 2004 John Wiley Sons, Ltd.
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