Abstract

The frequency and determinants of abnormal test performance by normal individuals are critically important to clinical inference. Here we compare two approaches to predicting rates of abnormal test performance among healthy individuals with the rates actually shown by 327 neurologically normal adults aged 18-92 years. We counted how many participants produced abnormal scores, defined by three different cutoffs with test batteries of varied length, and the number of abnormal scores they produced. Observed rates generally were closer to predictions based on a series of Monte Carlo simulations than on the binomial model. They increased with the number of tests administered, decreased as more stringent cutoffs were used to identify abnormality, varied with the degree of correlation among test scores, and depended on individual differences in age, education, race, sex, and estimated premorbid IQ. Adjusting scores for demographic variables and premorbid IQ did not reduce rates of abnormal performance. However, it eliminated the contribution of these variables to rates of abnormal test performance. These findings raise fundamental questions about the nature and interpretation of abnormal test performance by normal, healthy adults.

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