In this study, two statistical approaches for adjusting grades were tested on data obtained from four American law schools. These approaches were previously validated using data on undergraduates but have not been used in a study of postgraduate performance. Neither method yielded consistent improvements in the predictive validity of Law School Admission Test (LSAT) scores and undergraduate grades. The single exception was for School D, where a significant improvement in the correlation of test scores with law school grades was observed. It is hypothesized that the greater variability of LSAT scores in School D was the main reason for this result.
Get full access to this article
View all access options for this article.
References
1.
Boldt, R. F. (1976). Efficacy of undergraduate grade adjustment for improving the prediction of law school grades. (Report No. LSAC 76-4). In Law School Admissions Council, Reports of LSAC Sponsored Research: Vol. III, 1975-1977. Princeton, NJ: Law School Admissions Council.
2.
Cronbach, L. J. (1984). Essentials of psychological testing (4th ed.). New York: Harper & Row.
3.
Educational Testing Service . (1989-1994). Law school test. Princeton, NJ: Author.
4.
Elliott, R. , & Strenta, A. C. (1988). Effects of improving the reliability of the GPA on prediction generally and on comparative predictions for gender and race particularly. Journal of Educational Measurement, 25, 333-347.
5.
Linn, R. L. , & Hastings, C. N. (1984). A meta-analysis of the validity of predictors of performance in law school. Journal of Educational Measurement, 21, 245-259.
6.
Muraki, E. (1990). Fitting polytomous item response models to Likert-type data. Applied Psychological Measurement, 14, 59-71.
7.
Ramist, L. (1985). Validity of the ATP tests: Criterion-related validity. In Admissions Testing Program technical manual. New York: College Entrance Examination Board.
8.
Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika, Monograph Supplement No. 17.
9.
SAS Institute, Inc. (1985). SAS user's guide: Statistics, version 5 edition. Cary, NC: Author.
10.
Schrader, W. B. (1971). The predictive validity of College Board Admissions Tests. In W. H. Angoff (Ed.), The College Board Admissions Testing Program: A technical report on research and development activities relating to the Scholastic Aptitude Test. New York: College Entrance Examination Board.
11.
Searle, S. R. (1971). Linear models. New York: Wiley.
12.
Stricker, L. J. , Rock, D. A., Burton, N. W., Muraki, E., & Jirele, T. J. (1992). Adjusting college grade-point average for variations in grading standards (ETS RR No. 92-65). Princeton, NJ: Educational Testing Service.
13.
Thissen, D. (1988). MULTILOG, version 5.1 [Computer program]. Mooresville, IN: Scientific Software.
14.
Wilson, K. M. (1983). A review of research on the prediction of academic performance after the freshman year (College Board Report No. 83-2 and Educational Testing Service Research Report No. 83-11). New York: College Entrance Examination Board.
15.
Young, J. W. (1989). Developing a universal scale for grades: Investigating predictive validity in college admissions. Dissertation Abstracts International, 50, 1641A.
16.
Young, J. W. (1990). Adjusting the cumulative GPA using item response theory. Journal of Educational Measurement, 27, 175-186.
17.
Young, J. W. (1991a). Gender bias in predicting college academic performance: A new approach using item response theory. Journal of Educational Measurement, 28, 37-47.
18.
Young, J. W. (1991b). Improving the prediction of college performance of ethnic minorities using the IRT-based GPA. Applied Measurement in Education, 4, 229-239.
19.
Young, J. W. (1992). A general linear model approach to adjusting the cumulative GPA. Journal of Research in Education, 2, 31-37.
20.
Young, J. W. (1993). Grade adjustment methods. Review of Educational Research, 63, 151-165.
