| Literature DB >> 6332942 |
J Köbberling, K Richter, H Tillil.
Abstract
According to Bayes' rule the predictive value (PV) of a diagnostic test (= probability of disease if the test is positive) depends on the prevalence of the disease (= a priori probability), the sensitivity (c1) and the specificity (c2) of the test. A new variable has been introduced, the predictive factor (c), which is calculated as follows: c = c1/(c1 +1 -c2). Since the PV only depends on this factor and on the prevalence, the calculation is much easier and a general graphical solution is possible. This simplification renders several additional advantages and facilitates the understanding of the dependence of PV on prevalence.Mesh:
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Year: 1984 PMID: 6332942 DOI: 10.1007/bf01728177
Source DB: PubMed Journal: Klin Wochenschr ISSN: 0023-2173