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The diagnostic utility of multiple-level likelihood ratios

Published online by Cambridge University Press:  01 September 2009

STEPHEN C. BOWDEN*
Affiliation:
Department of Psychology, The University of Melbourne, Victoria, Australia
DAVID W. LORING
Affiliation:
Department of Neurology, Emory University School of Medicine, Atlanta, Georgia
*
*Correspondence and reprint requests to: Stephen C. Bowden, Department of Psychology, University of Melbourne, Parkville, Victoria, Australia 3052. E-mail: sbowden@unimelb.edu.au

Abstract

Clinicians are accustomed to interpreting diagnostic test scores in terms of sensitivity and specificity. Many clinicians also appreciate that sensitivity and specificity need to be interpreted in terms of local base rates (i.e., pretest probability). However, most neuropsychological tests contain a wide range of scores. Important diagnostic information may be sacrificed when valid test scores are reduced to the simple dichotomy of “positive” or “negative” diagnosis that underlies sensitivity and specificity analysis. The purpose of this study is to provide an introduction to multiple-level likelihood ratios, a method for preserving the information in a wider range of scores. These statistics are first described using a hypothetical example of dementia screening, then with patient data from an epilepsy surgery sample. Multiple-level likelihood ratios have several advantages over sensitivity and specificity analysis because they are applied across a wider range of diagnostic scores, and generalize to settings with different base rates. We suggest that the diagnostic validity of many psychological tests may be underestimated by relying solely on traditional dichotomous sensitivity and specificity analysis. (JINS, 2009, 15, 769–776.)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2009

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