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The Polygraph and Lie Detection
and may also have different standard deviations (a measure of spread). To extrapolate an ROC curve from only one point using this Gaussian model requires that we additionally assume these standard deviations are equal. Figure H-2 shows six theoretical ROCs from this “equivariance” binormal model, with respective A values of 0.5, 0.6, 0.7, 0.8, 0.9, 0.95, along with the reverse diagonal line corresponding to sensitivity = (1– false positive rate), which can alternately be interpreted as false positive rate = false negative rate. On this line, the probability that the test is correct is the same whether the examinee is deceptive or nondeceptive. The intersection of each ROC with this line highlights the difference be-
FIGURE H-2 Six theoretical ROC curves from the “equivariance” binormal model.
NOTE: Curves are binormal equivalence ROCs with accuracy index (A) values of 0.5, 0.6, 0.7, 0.8, 0.9, and 0.95.