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Using Empirical Bayes Techniques in the Law School Validity Studies
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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Citations
Cites
Bayes Estimates for the Linear Model
Lindley, D. V., & Smith, A. F. M. (1972) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1972.tb00885.x · Cited by 2,025
Cited by
Explaining Fixed Effects: Random Effects Modeling of Time-Series Cross-Sectional and Panel Data
Bell, A., & Jones, K. (2015) · Political Science Research and Methods · doi:10.1017/psrm.2014.7 · Cited by 1,515
Parametric empirical Bayes inference: theory and applications
Morris, C. N. (1983) · Journal of the American Statistical Association · doi:10.1080/01621459.1983.10477920 · Cited by 1,448
Latent Variable Modeling in Heterogeneous Populations
Muthén, B. O. (1989) · Psychometrika · doi:10.1007/bf02296397 · Cited by 1,008
Hunter, J. E., & Schmidt, F. L. (2000) · International Journal of Selection and Assessment · doi:10.1111/1468-2389.00156 · Cited by 833
Schmidt, F. L., Oh, I., & Hayes, T. L. (2009) · British Journal of Mathematical and Statistical Psychology · doi:10.1348/000711007x255327 · Cited by 708
Metadata
- Authors
- Rubin, D. B.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- 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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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.