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• #### Index 381-398

BOX 2-1 Terms Relevant to Measuring the Accuracy of Polygraph Testing

The table below shows the four possible combinations of actual truthfulness and polygraph test results. The text under the table defines terms that are used to describe the quantitative relationships among these outcomes.

 True Condition Test Result Positive (truly deceptive) Negative (truly truthful) Total Positive (testing deceptive) a true positive b false positive a + b Negative (testing truthful) c false negative d true negative c + d Total (n) a + c b + d a + b + c + d

Sensitivity—The proportion of truly positive (deceptive) cases that give positive results on the test (a/[a + c]). This is also known as the conditional probability of a true-positive test or the true-positive proportion.

False negative probability—The proportion of truly positive cases that give negative results on the test (c/[a + c]). This quantity is the conditional probability of a false-negative test and is the complement of sensitivity (that is, the difference between sensitivity and 100 percent).

Specificity—The proportion of truly negative (truthful) cases that give negative results on the test (d/[b + d]). This quantity is also known as the conditional probability of a true-negative test.

False positive probability—The proportion of truly negative cases that give positive results on the test (b/[b + d]). This quantity is the conditional probability of a false-positive test and is the complement of specificity.

Three terms use test results as a reference point and reveal how well the test results indicate the true conditions (see text for further discussion).

Positive predictive value—The predictive value of a positive test, that is, the percentage of positive tests that are correct (a/[a + b]).

Negative predictive value—The predictive value of a negative test, that is, the percentage of negative tests that are correct (d/[c + d]).

False positive index—Number of false positives for each true positive (b/a). This is another way of conveying the information described by positive predictive value, in order to make clearer the tradeoffs between false positives and true positives.

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