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Predictive value of tests is the probability of a target condition given by the result of a test, often in regard to medical tests.

• In cases where binary classification can be applied to the test results, such yes versus no, test target (such as a substance, symptom or sign) being present versus absent, or either a positive or negative test), then each of the two outcomes has a separate predictive value. For example, for positive or negative test, the predictive values are termed positive predictive value or negative predictive value, respectively.
• In cases where the test result is of a continuous value, the predictive value generally changes continuously along with the value. For example, for a pregnancy test that displays the urine concentration of hCG, the predictive value increases with increasing hCG value.

A conversion of continuous values into binary values can be performed, such as designating a pregnancy test as "positive" above a certain cutoff value, but this confers a loss of information and generally results in less accurate predictive values.

For more information on conversion and its disadvantages, see Artificial binary classification.

See also

• Positive predictive value
• Negative predictive value