Bayes' rule for clinicians: an introduction

Bayes' Rule is a way of calculating conditional probabilities. It is difficult to find an explanation of its relevance that is both mathematically comprehensive and easily accessible to all readers. This article tries to fill that void, by laying out the nature of Bayes' Rule and its impli...

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Bibliographic Details
Published inFrontiers in psychology Vol. 1; p. 192
Main Author Westbury, Chris F
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Research Foundation 01.01.2010
Frontiers Media S.A
Subjects
bayes rule
conditional probablity
diagnosis
formal methods in diagnosis
probability theory
Psychology
Bayes theory
diagnosis
base rates
probability
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Summary:Bayes' Rule is a way of calculating conditional probabilities. It is difficult to find an explanation of its relevance that is both mathematically comprehensive and easily accessible to all readers. This article tries to fill that void, by laying out the nature of Bayes' Rule and its implications for clinicians in a way that assumes little or no background in probability theory. It builds on Meehl and Rosen's (1955) classic paper, by laying out algebraic proofs that they simply allude to, and by providing extremely simple and intuitively accessible examples of the concepts that they assumed their reader understood.
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Edited by: Edward Callus, IRCCS Policlinico San Donato, Italy
Reviewed by: Gianluca Castelnuovo, Università Cattolica del Sacro Cuore, Italy; Gian Mauro Manzoni, Istituto Auxologico Italiano IRCCS, Italy; Francesco Pagnini, University of Bergamo, Italy
This article was submitted to Frontiers in Psychology for Clinical Settings, a specialty of Frontiers in Psychology.
ISSN:1664-1078
1664-1078
DOI:10.3389/fpsyg.2010.00192