Predictive values are the probability of correctly identifying a subject's condition given the test result.
Predictive values use Bayes' theorem along with a pre-test prior probability (such as the
prevalence of the condition in the population) and the sensitivity and specificity of the test to
compute the post-test probability (predictive value).
The positive predictive value is the probability that a subject has the condition given a
positive test result; the negative predictive value is the probability that a subject does not
have the condition given a negative test result.