Appendix H explains how we estimated the ROC curves and values of A. It also presents additional descriptive statistics on these A values.


Two published meta-analyses claim to find associations between accuracy and characteristics of the studies, and therefore deserve discussion. In one, Kircher and colleagues (1988) reported that polygraph accuracy (measured as Pearson’s r between test results and actual truthfulness or deception) was correlated with three study characteristics across 14 polygraph studies of comparison question tests. The characteristics were examinee population (college students or others), incentive strength (the presence or absence of a tangible consequence of being judged deceptive, for both innocent and guilty examinees), and whether or not the study used field testing techniques that allowed examiners to conduct three or more charts in order to get a conclusive result. Because these characteristics were highly correlated with each other in the 14 studies, and with whether or not the studies were conducted in the authors’ laboratory, it is difficult to attribute the observed associations to any specific characteristic. We do not place much confidence in the reliability of the correlations because of the instability of the estimates for such a small number of studies and because of the inherent limits of Pearson’s r as an index of polygraph accuracy. Moreover, our examination of one of these variables (strength of incentive) failed to reveal an association with test accuracy in our sample of studies, which is larger and covers a broader range of incentives. Kircher and colleagues coded incentive strength as high for studies that offered as little as a $5 bonus to examinees for producing a nondeceptive result; only one study in the Kircher meta-analysis involved an incentive stronger than a $20 bonus. In the other meta-analysis, Ben-Shakhar and Elaad (2002b) examined 169 experimental conditions from 80 laboratory studies of concealed information tests. The study included a large number of studies that did not meet our quality criteria or that we did not use to estimate accuracy because they did not include a comparison group that lacked any concealed information. Its overall results were generally consistent with ours, but it did find positive associations of accuracy with three moderator variables: number of sets of relevant and comparison questions, the presence of motivational instructions or monetary incentives, and the presence of the requirement that deceptive examinees make a deceptive answer (rather than a nonresponse). We cannot compare their results directly with ours because of the large number of studies that support their analysis of moderator variables that are not in our dataset. For example, all but one of the studies covered in this meta-analysis that are also in our dataset were coded by Ben-Shakhar and Elaad as positive for the motivation variable. These meta-analyses cover only laboratory studies, so their relevance to field practice is uncertain.


As stated in Note 2, Kircher et al. (1988) evaluated only 14 studies and considered bonuses of $5 to $20 as strong motivations. Ben-Shakhar and Elaad (2002) included a considerable number of studies in their analysis that did not meet our basic quality criteria or that we excluded from our analysis because they lacked a comparison group of examinees who had no concealed information. We consider their evidence suggestive of a motivation effect but not definitive.


This study shares important features with true screening studies and with specific-incident studies. The questions are broader in scope than in a traditional specific-incident study, but still deal with specific, discrete, and potentially verifiable events. For example, one relevant question in this study was “Have you been convicted of a felony in the state of Georgia?” There is little room for ambiguity in interpreting the question or the answer, in contrast with typical screening questions, which are more

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