While an admission test may strongly predict success in university or law school programs for most test takers, there may be some test takers who are mismeasured. To address this issue, a class of statistics called person-fit statistics is used to check the validity of individual test scores. However, most person-fit statistics are designed for a single test, and not much is known about the performance of these statistics for admission tests consisting of multiple highly correlated subtests. In this study, the performance of a number of person-fit statistics was evaluated based on data that simulated aberrant responding on highly correlated subtests. The results indicated that two of the statistics outperformed the others.