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Peer reviewedSchoenfeldt, Lyle F.; Lissitz, Robert W. – American Educational Research Journal, 1974
(See also TM 501 087, TM 501 088, TM 501 090.)
Descriptors: Bayesian Statistics, Models, Multiple Regression Analysis, Prediction
Peer reviewedNovick, Melvin R. – American Educational Research Journal, 1974
(See also TM 501 087, TM 501 088, and TM 501 089.)
Descriptors: Bayesian Statistics, Models, Multiple Regression Analysis, Prediction
Moderator Subgroups for the Estimation of Educational Performance: A Comparison of Prediction Models
Peer reviewedLissitz, Robert W.; Schoenfeldt, Lyle F. – American Educational Research Journal, 1974
The purpose of this study was to compare five predictor models, including two least-square procedures, two probability weighting (semi-Bayesian) methods, and a Bayesian model developed by Lindley. (See also TM 501 088, TM 501 089, and TM 501 090) (Author/NE)
Descriptors: Bayesian Statistics, College Freshmen, Models, Multiple Regression Analysis
Peer reviewedShigemasu, Kazuo – Journal of Educational Statistics, 1976
Context for the application and specialization of a Bayesian linear model is m-group regression and the application to the prediction of grade point average. Specialization involves the assumption of homogeneity of regression coefficients (but not intercepts) across groups. Model's predictive efficiency is compared with that of the full m-group…
Descriptors: Bayesian Statistics, Comparative Analysis, Grade Point Average, Least Squares Statistics
Peer reviewedNovick, Melvin R.; Jackson, Paul H. – American Educational Research Journal, 1974
(See also TM 501 087, TM 501 089 and TM 501 090.)
Descriptors: Bayesian Statistics, Models, Multiple Regression Analysis, Prediction
Download full textNovick, Melvin R.; And Others – 1971
The feasibility and effectiveness of a Bayesian method for estimating regressions in m groups is studied by application of the method to data from the Basic Research Service of The American College Testing Program. Evidence supports the belief that in many testing applications the collateral information obtained from each subset of m-1 colleges…
Descriptors: Academic Achievement, Bayesian Statistics, College Students, Colleges
Hinkle, Dennis E.; Polhamus, Edward C. – 1980
Classical multiple regression was compared with Bayesian m-group regression, complete with cross-validation. The setting was a post-developmental studies situation in a comprehensive community college. A secondary purpose of the study was to incorporate an advisor prediction of grade point average (GPA) as input into both regression procedures.…
Descriptors: Bayesian Statistics, Community Colleges, Developmental Studies Programs, Grade Point Average
Lunneborg, Clifford E. – 1971
A Bayesian prediction strategy is outlined in which antecedent measures are divided into two subgroups. One subgroup is used to discriminate among criterion groups, the second to provide normal linear predictions for each group. Individualized regression constants are subsequently obtained by computing probabilities of group membership from the…
Descriptors: Academic Achievement, Achievement Tests, Aptitude Tests, Bayesian Statistics
