LSAT Technical Reports

Analysis of Differential Prediction of Law School Performance by Gender Subgroups Based on 2008–2010 Entering Law School Classes (TR 13-01)

In the law school admission process, it is essential that the criteria used for admission be fair to all subgroups in the applicant population. One method used to evaluate the fairness of the admission process is to compare the predicted against the actual first-year averages (FYAs) within individual law schools for various subgroups of the applicant population. The purpose of this study is to address questions of differential prediction between male and female first-year law school students based on data for the 2008, 2009, and 2010 entering classes of 188 law schools. The data were available from correlation studies sponsored by the Law School Admission Council.

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 conducted separately for all law schools included in the study, resulting in three prediction equations for each individual law school.

None of the three prediction equations evaluated were deemed to be problematic. That is, none of the prediction equations significantly overpredicted or underpredicted FYAs for male or female students across the schools studied. The magnitude of overprediction or underprediction across members of each gender subgroup was found to be less than one tenth of a standard deviation, on average, for each prediction equation. The degree of differential prediction was greatest for the model using UGPA alone, but these differences were still too small to be of practical significance. As an illustration, consider a law school that has a grading scale from 0 to 4.33 with an observed mean of 3 and standard deviation of 0.44. Then, for example, an underprediction of one tenth of a standard deviation for female students at such a law school would mean that their FYAs were underpredicted on average by a factor of 0.044. Overall, the results of this study do not support the concern that the use of LSAT scores or the traditional combination of LSAT score and UGPA results 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. That is, the performance of individuals within a subgroup whose FYAs are overpredicted on average may still be underpredicted, and vice versa.

In summary, 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 score, UGPA, or a combination of those two measures unfairly predict future law school performance for either gender subgroup.

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Additional reports in this collection

LSAT Performance With Regional, Gender, and Racial and Ethnic Breakdowns: 2011–2012 Through 2017–2018 Testing Years

The purpose of this report is to provide summary information about Law School Admission Test (LSAT) performance, including performance classified by country, region of the United States, gender only, race and ethnicity only, and both gender and race and ethnicity. Information regarding LSAT performance is summarized for the 2011–2012 through 2017–2018 testing years and compiled into a single report, enabling trends with regard to the performance and representation of various subgroups to be examined.

Summary of 2017, 2018, and 2019 LSAT Correlation Study...

Since the inception of the Law School Admission Test (LSAT), the Law School Admission Council (LSAC) has sought to evaluate and ensure its validity for use in the law school admission process. As predictive validity is an important component in the overall evaluation of test validity, LSAC has carried out predictive validity studies, also called LSAT Correlation Studies, since the test was first administered.