Analysis of Differential Prediction of Law School Performance by Racial/Ethnic Subgroups Based on 2002-2004 Entering Law School Classes (TR-06-01)
by Lynne L. Norton, Deborah A. Suto and Lynda M. Reese
In the law school admission process, it is essential that the criteria used for admission are fair to all subgroups in the applicant population. One method used to evaluate the fairness of the admission process is to compare the predicted and actual first-year averages (FYAs) within individual law schools for various subgroups of the applicant population. The current study was designed to address questions of differential prediction of law school grades for various racial/ethnic subgroups.
The sample used in this study was drawn from the 2002, 2003, and 2004 entering law school classes, using data that were available from the Law School Admission Council (LSAC)-sponsored Correlation Studies. Data were analyzed from 183 law schools, each of which enrolled, over the three-year period, 10 or more first-year students who identified themselves as Asian American, Black, or Latino.
Statistical analyses were used to predict FYAs using Law School Admission Test (LSAT) score alone, undergraduate grade-point average (UGPA) alone, and the best predictive combination of LSAT score and UGPA. Analyses were carried out separately for all individual law schools included in the study, resulting in three prediction equations for each law school.
The results of the analyses indicate that FYA tended to be, on average, slightly overpredicted (i.e., predicted FYAs exceeded actual FYAs) for all three of the minority subgroups studied here, with Black law students exhibiting the most overprediction and Asian American law students exhibiting the least overprediction. The use of a combination of both LSAT scores and UGPAs provided the least amount of overprediction for minority subgroups on the school level than did use of a single predictor alone. Overall, these results do not support the concern that the LSAT score or the traditional combination of LSAT score and UGPA may contribute toward unfair admission decisions for the racial/ethnic subgroups studied here.
While considering the results of this study, the reader should keep in mind that they refer only to subgroup behavior and not to individuals. For example, while results may suggest that UGPAs alone may overpredict FYAs for Black law students on average, the performance of many individual Black law students may be underpredicted based solely on their UGPAs.
Finally, it is worth repeating that the average amount of overprediction or underprediction of FYAs found for the four racial/ethnic subgroups studied was very slight, regardless of the prediction equation that was used. In other words, this study provided no evidence that LSAT scores, UGPAs, or combinations of those two measures unfairly predict future law school performance for any racial/ethnic subgroup.