In screening and diagnostic tests, the probability that a person with a positive test is a true positive (i.e., does have the disease), or that a person with a negative test truly does not have the disease. The predictive value of a screening test is determined by the sensitivity and specificity of the test, and by the prevalence of the condition for which the test is used. ( Diagnosis) To Calculation

The posttest probability that a condition is present based on the results of a test.

The probability that a person with a positive test for a disease truly has the disease, or that a person with a negative test truly does not have it.

Statistics: A positive predictive value expresses the probability that a test gives a true result for a true statistic. A negative predictive value expresses the probability that a test gives a false result for a false statistic.

The probability that an animal with a positive test result does have the disease and one with a negative test result does not have the disease. This is determined by the prevalence of the condition and the sensitivity and specificity of the test. It can be expressed in two ways: the Positive Predictive Value and the Negative Predictive Value. These two values are not exact opposites..

Proportion of animals that test negative in an assay that are truly uninfected; predictive value is influenced by diagnostic sensitivity and specificity, as well as prevalence of infection..

Percentage of positive results that are true positives or of negative results that are true negatives. Galen and Gambino, 1975 RT sensitivity, specificity