considers nonlaboratory components of medical diagnosis as informal tests within an information collection sequence. By comparison with parallel tests, serial tests are cost-effective because the most powerful and expensive tests are not performed on many examinees. A serial test usually begins with relatively inexpensive and noninvasive measures and proceeds to more expensive and more invasive procedures as the accumulation of information makes the presence of the feature of interest increasingly likely. One can imagine a polygraph test as the first step in a personal security screening sequence, with more expensive background checks, detailed interrogations, and possibly levels of surveillance as later stages in the process. Indeed, at least one agency uses serial polygraph testing, where positive results of one type of test lead to a second test of somewhat different nature, and so on.

The accuracy of serial combination testing is much like that for parallel combination testing but with the roles of sensitivity and specificity— and, hence, of false positive and false negative rates—reversed. The feature of interest is not diagnosed unless all tests are positive, so the sensitivity of the serial combination is the product of the sensitivities of the component tests, and the false positive rate of the serial combination is the product of the false positive rates of the individual component tests. Thus, serial testing yields a combination with lower sensitivity but higher specificity than its components. In general, specificity drives the false positive index, and so positive serial tests are often used in medical care to arrive at a firm basis for taking action. As with parallel testing, the potential gain in accuracy of serial testing is limited by the accuracy and extent of dependence of each additional test added to the sequence. In contrast with parallel testing, however, each rearrangement of the ordering of a given set of tests yields a new serial test with different properties from other orderings of the component tests.

For personnel security screening, the relative inexpensiveness of polygraph makes it attractive as an early step in a serial screening process. But this requires other suitable tests with known degrees of accuracy for follow-up. Moreover, if one wanted to avoid large numbers of false positives and the associated costs of following them up, polygraph testing would have to be used at a high specificity, incurring the risk of early termination of the screening sequence for some serious security risks.


In contrast to the above approaches, nonstatistical expert systems typically codify and represent existing knowledge using collections of rules, for instance, of the form “if-then-else,” with deterministic or subjective probabilistic outcomes and heuristic “inference engines” for operat-

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