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→By predictive values: someone got confused by double negatives in explaining what negative predictive value means. |
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Pretest probability = (True positive + False negative) / Total sample
Also, in this case, the ''positive post-test probability'' (the probability of having the target condition if the test falls out positive), is numerically equal to the [[positive predictive value]], and the ''negative post-test probability'' (the probability of not having the target condition if the test falls out negative) is numerically complementary to the [[negative predictive value]] (<nowiki>[</nowiki>negative post-test probability<nowiki>]</nowiki> = 1 - <nowiki>[</nowiki>negative predictive value<nowiki>]</nowiki>),<ref name=ebell>[http://ebp.uga.edu/ebp-modules/ Evidence-Based Practice Online Course] By Mark Ebell. College of Public Health, University of Georgia. Retrieved Aug 2011</ref> again assuming that the individual being tested does not have any other risk factors that result in that individual having a different ''pre-test probability'' than the reference group used to establish the positive and negative predictive values of the test.
In the diagram above, this ''positive post-test probability'', that is, the posttest probability of a target condition given a positive test result, is calculated as:
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