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Cited by 162

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Using Empirical Bayes Techniques in the Law School Validity Studies

Rubin, Donald B.·1980·Journal of the American Statistical Association

Abstract

The law school validity studies are primarily concerned with the prediction of first-year average in law school from Law School Aptitude Test score and undergraduate grade point average. Traditionally, a separate admitting equation is estimated in each law school by the method of least squares based on data from students who attended the law school in recent years. These least squares equations can fluctuate rather wildly from year to year. This study employs empirical Bayes techniques to obtain admitting equations that are better than the least squares admitting equations in two ways: for each law school, the empirical Bayes admitting equations are more stable in time than the least squares admitting equations; and the empirical Bayes admitting equations predict student performance more accurately than the least squares admitting equations.

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Metadata

Authors
Rubin, D. B.
Venue
Journal of the American Statistical Association
Published
1980-12
Volume
75
Issue
372
Pages
801-816
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
OpenAlex
W2084625156
Cited by
162
References
1
FWCI
9.47
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Using Empirical Bayes Techniques in the Law School Validity Studies. https://app.cochat.ai/papers/10.1080/01621459.1980.10477553
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Rubin, D. B. (1980). Using Empirical Bayes Techniques in the Law School Validity Studies. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.1980.10477553

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.