Research Reports

A New Approach to Detecting Cluster Aberrancy (RR 16-05)

This report addresses a general type of cluster aberrancy in which a subgroup of test takers has an unfair advantage on some subset of administered items. Examples of cluster aberrancy include item preknowledge and test collusion. In general, cluster aberrancy is hard to detect due to the multiple unknowns involved: Unknown subgroups of test takers have an unfair advantage on unknown subsets of items. The issue of multiple unknowns makes the detection of cluster aberrancy a challenging problem from the standpoint of applied mathematics. This report presents a novel algorithm to detect cluster aberrancy. The algorithm is general and applicable to all types of testing programs: paper-and-pencil testing, computer-based testing, multistage testing, and computerized adaptive testing; it can also be applied in areas outside of psychometrics, such as finance (e.g., detecting financial fraud). Both simulated and real data were used to study the performance of this algorithm.

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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.