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Suen, Hoi K. – Evaluation and the Health Professions, 1984
The Bayesian inferential process is modified for use in an aggregate meta-analytic evaluation. Compared with the average effect size meta-analytic approach, the Bayesian approach was more sensitive, more consistent and more powerful. This approach is recommended when primary data are not available and when all evaluations involve comparisons of…
Descriptors: Bayesian Statistics, Data Interpretation, Effect Size, Evaluation Methods
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Shigemasu, 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
Vos, Hans J. – 1997
The purpose of this paper is to formulate optimal sequential rules for mastery tests. The framework for this approach is derived from empirical Bayesian decision theory. Both a threshold and linear loss structure are considered. The binomial probability distribution is adopted as the psychometric model involved. Conditions sufficient for…
Descriptors: Bayesian Statistics, Concept Formation, Cutting Scores, Foreign Countries
Glas, Cees A. W.; Vos, Hans J. – 2000
This paper focuses on a version of sequential mastery testing (i.e., classifying students as a master/nonmaster or continuing testing and administering another item or testlet) in which response behavior is modeled by a multidimensional item response theory (IRT) model. First, a general theoretical framework is outlined that is based on a…
Descriptors: Adaptive Testing, Bayesian Statistics, Classification, Computer Assisted Testing
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Novick, 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
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Novick, Melvin R.; And Others – Psychometrika, 1973
This paper develops theory and methods for the application of the Bayesian Model II method to the estimation of binomial proportions and demonstrates its application to educational data. (Author/RK)
Descriptors: Bayesian Statistics, Educational Testing, Mathematical Models, Measurement
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Arkes, Hal R. – Journal of Consulting and Clinical Psychology, 1981
Five impediments to accurate clinical judgment are discussed: inability to assess covariation, influence of preconceived notions, lack of awareness of one's judgmental processes, overconfidence, and hindsight bias. Presents three strategies to minimize impediments' effects: considera- tion of alternative outcomes, increased attention to data, and…
Descriptors: Analysis of Covariance, Bayesian Statistics, Bias, Clinical Diagnosis
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Larson, Richard C.; Kaplan, Edward H. – New Directions for Program Evaluation, 1981
Evaluation is discussed as an information-gathering process. Currently popular evaluation programs are reviewed in relation to decision making and various approaches that seem to contribute to the decision utility of evaluation (e.g. classical approaches, Bayesian approaches, adaptive designs, and model-based evaluations) are described. (Author/AL)
Descriptors: Bayesian Statistics, Decision Making, Evaluation Methods, Formative Evaluation
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Wilcox, Rand R. – Journal of Educational Statistics, 1979
Methods are described for obtaining upper and lower bounds to both false-positive and false-negative decisions with a mastery test. These methods make no assumptions about the form of the true score distribution. (CTM)
Descriptors: Bayesian Statistics, Cutting Scores, Mastery Tests, Mathematical Formulas
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Haig, Brian D. – Australian Journal of Education, 1996
This paper argues that statistical inference practices in both educational and psychological research should be directed away from traditional significance tests in favor of Bayesian inferential methods. Regular use of exploratory data analytic methods is recommended in conjunction with computer intensive resampling methods. Approaches to…
Descriptors: Bayesian Statistics, Educational Change, Educational Research, Foreign Countries
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Berger, Martijn P. F.; Veerkamp, Wim J. J. – Journal of Educational and Behavioral Statistics, 1997
Some alternative criteria for item selection in adaptive testing are proposed that take into account uncertainty in the ability estimates. A simulation study shows that the likelihood weighted information criterion is a good alternative to the maximum information criterion. Another good alternative uses a Bayesian expected a posteriori estimator.…
Descriptors: Ability, Adaptive Testing, Bayesian Statistics, Computer Assisted Testing
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Lin, Miao-Hsiang; Hsiung, Chao A. – Psychometrika, 1994
Two simple empirical approximate Bayes estimators are introduced for estimating domain scores under binomial and hypergeometric distributions respectively. Criteria are established regarding use of these functions over maximum likelihood estimation counterparts. (SLD)
Descriptors: Adaptive Testing, Bayesian Statistics, Computation, Equations (Mathematics)
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Weiss, Robert – Evaluation Review, 1994
Coping style and effects of counseling intervention on pain tolerance was studied for 61 elementary school students through immersion of hands in cold water. Bayesian predictive inference tools are able to distinguish between subject characteristics and manipulable treatments. Sensitivity analysis strengthens the certainty of conclusions about…
Descriptors: Attention, Bayesian Statistics, Children, Coping
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Massaro, Dominic W.; Friedman, Daniel – Psychological Review, 1990
Several models of information integration are developed and analyzed in the context of a prototypical pattern-recognition task. Evaluation, integration, and decision-making processes are specified for each. Simulations and predictions are carried out to provide a measure of identifiability or extent to which they can be distinguished from one…
Descriptors: Bayesian Statistics, Cognitive Processes, Criteria, Decision Making
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Henderson, Pamela W.; Buchanan, Bruce – Psychometrika, 1992
An extension is described to a product-testing model to account for misinformation among subjects that would lead them to perform incorrectly on "pick one of two" tests. The model is applied to a data set of 367 subjects picking 1 of 2 colas. Misinformation does exist. (SLD)
Descriptors: Adults, Bayesian Statistics, Consumer Economics, Equations (Mathematics)
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