Bayes' Rule for Clinicians
An Introduction
Bibliographic Data
| ID | 5829565 |
|---|---|
| Authors | Chris Westbury (0000-0001-7788-0278, University of Alberta, corresponding author) |
| Year | 2010 |
| Volume | 1 |
| Publication date | 2010-01-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Psychology (JOURNAL) |
| Journal identifiers | ISSN: 1664-1078 • E-ISSN: 1664-1078 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fpsyg.2010.00192 |
| PMID | 21833252 |
| PMCID | PMC3153801 |
| OpenAlex | W2121833919 |
| Language | EN |
| References cited | 1 |
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 & 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, and provides examples of how the rule applies in a variety of clinical settings
| Citation velocity | historical |
|---|---|
| Highly cited | No |