Analysis of Differential Prediction of Law School Performance by Gender Subgroups Based on 1999–2001 Entering Law School Classes (TR-03-04)
by Jennifer R. Duffy and Peter J. Pashley

Executive Summary

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 grade-point averages (FYAs) at each law school for various subgroups of the applicant population. The purpose of the current study is to address questions of differential prediction between male and female first-year law school students based on data from the 1999, 2000, and 2001 entering classes of 177 law schools.

Statistical analyses were used to predict FYAs using three traditional predictors: undergraduate grade-point average (UGPA), Law School Admission Test (LSAT) score, and the best predictive combination of UGPA and LSAT score. A separate analysis was conducted for each law school included in the study (i.e., three prediction equations were derived for each individual law school included in this study).

The prediction equations that incorporated both LSAT scores and UGPAs typically provided the least amount of differential prediction on the school level between male and female students. The magnitude of the difference was approximately the same as when LSAT was used alone, but the combination of LSAT and UGPA resulted in a higher number of schools within one point of zero (i.e., a tenth of a standard deviation). When UGPA was used as the sole predictor variable, FYA tended to be underpredicted on average for male students and overpredicted on average for female students. When LSAT alone was used to predict FYA, some underprediction of female FYA mean and some overprediction of male FYA mean was observed. For all three of the prediction equations, the magnitude of the over- and underprediction that did occur was very small. Overall, the results of this study do not support the concern that the use of LSAT scores or the traditional combination of LSAT scores and UGPAs result in unfair admission decisions with regard to gender.

While considering the results of this study, the reader should keep in mind that the results refer only to subgroup behavior and not to individuals. For example, while results may suggest that UGPAs alone may overpredict FYAs for female law students on average, the performance of many individual female law students will be underpredicted based solely on their UGPAs.

Finally, it is worth repeating that the average amount of overprediction or underprediction of FYAs found was always very small, 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 either gender subgroup.

Analysis of Differential Prediction of Law School Performance by Gender Subgroups Based on 1999–2001 Entering Law School Classes (TR-03-04)

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