Research Reports

Response Times in a Bayesian Marginal Modeling Framework (RR 18-02)

A new statistical model is proposed to study the effects of various testing conditions on a population of test takers. This flexible model allows for numerous effects to be considered simultaneously. A Bayesian approach is employed, taking prior information into consideration. An empirical example demonstrates the utility of the suggested model to test the influence of item presentation formats on the performance of test takers. This research could be of practical value in a potential transition of the Law School Admission Test (LSAT) from a paper-and-pencil format to a digital mode.

Request the full report

Additional reports in this collection

researchers study paperwork and examine charts and figures on a tablet

Evidence to Support Validity Claims for Using LSAT Scores...

Law School Admission Test (LSAT) scores provide a standard measure of an applicant’s proficiency in a well-defined set of important skills associated with success in law school coursework. LSAT scores are also a strong predictor of first-year grades (FYG) and cumulative grade point average (CGPA) in law school. The most recent correlational study of LSAT results (2019) shows that LSAT scores are far superior to undergraduate grade point average (UGPA) in predicting FYG...

Understanding and Interpreting Law School Enrollment Data...

The Law School Admission Council (LSAC) has a long-standing commitment to diversity, equity, and inclusion in legal education and in the legal profession. In line with its mission to promote quality, access, and equity in legal education, LSAC is providing this report, Understanding and Interpreting Law School Enrollment Data: A Focus on Race and Ethnicity, to help law schools, admission professionals, and other legal education stakeholders understand how we are measuring who is the pipeline.