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Research Library

All reports in LSAC’s Research Library are available upon request. Executive summaries are available below for the latest LSAT Technical Reports and other research published within the last 10 years.

Looking for older reports? Consult the Research Archive

Current Research:

In an analysis of 2024-2025 test taker data, the LSAC research team provides insights into when test takers first thought about going to law school, what motivates them to pursue law school, and more.
Through the Post LSAT Questionnaire, future law applicants provide numerous insights for how to better support and promote their aspirations. This report, the first in a series, focuses on how 2023-2024 test takers see their path to a legal education.
The LSAC Prelaw Undergraduate Scholars (PLUS) Program highlights the need for intentionality in how we use research, student feedback, and data in pipeline development.

Item response theory (IRT) is a mathematical model used to support the development, analysis, and scoring of tests and questionnaires. For example, IRT allows for the description of item (i.e., question) characteristics, such as difficulty, as well as the proficiency level of test takers. Various IRT models are available, and choosing the most appropriate model for a particular test is essential. Since the fit of the test data to the chosen model is never perfect, measuring the fit of the model to the data is imperative.

Item response theory (IRT) is a mathematical model that is often applied in the development and analysis of educational and psychological assessments. Various IRT models exist, and practitioners must choose the model that is most appropriate for their particular assessment. Even when the most appropriate model is applied, the fit of the assessment data to the model is rarely perfect in practice. How serious, then, is model misfit for practical decision-making?