CHRISTOPHER M REMBOLD, M.D.; DENNY WATSON, Ph.D.
This article reintroduces a different form of Bayes' theorem that allows calculation of posttest probabilities by adding quantities known as "weights." A weight combines information found in both a test's sensitivity and specificity. A single value can describe how a given test result changes the posttest probability of disease. The use of weights and this form of Bayes' theorem should allow more widespread understanding and use of probability theory in clinical practice.
REMBOLD CM, WATSON D. Posttest Probability Calculation by Weights: A Simple Form of Bayes' Theorem. Ann Intern Med. ;108:115–120. doi: 10.7326/0003-4819-108-1-115
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Published: Ann Intern Med. 1988;108(1):115-120.
Cardiology, Coronary Risk Factors, Hypertension, Nephrology.
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Print ISSN: 0003-4819 | Online ISSN: 1539-3704
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