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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
Alcala-Quintana, Rocio; Garcia-Perez, Miguel A. – Psychological Methods, 2004
Variants of adaptive Bayesian procedures for estimating the 5% point on a psychometric function were studied by simulation. Bias and standard error were the criteria to evaluate performance. The results indicated a superiority of (a) uniform priors, (b) model likelihood functions that are odd symmetric about threshold and that have parameter…
Descriptors: Psychometrics, Computation, Error of Measurement, Bayesian Statistics
Gao, Furong; Chen, Lisue – Applied Measurement in Education, 2005
Through a large-scale simulation study, this article compares item parameter estimates obtained by the marginal maximum likelihood estimation (MMLE) and marginal Bayes modal estimation (MBME) procedures in the 3-parameter logistic model. The impact of different prior specifications on the MBME estimates is also investigated using carefully…
Descriptors: Simulation, Computation, Bayesian Statistics, Item Analysis
Steinheiser, Frederick H., Jr.; Hirshfeld, Stephen L. – 1978
The scientific implications and practical applications of the Stein estimator approach for estimating true scores from observed scores are of potentially great importance. The conceptual complexity is not much greater than that required for more conventional regression models. The empirical Bayesian aspect allows the examiner to incorporate…
Descriptors: Bayesian Statistics, Goodness of Fit, Mathematical Models, Measurement
Novick, Melvin R. – 1971
An interactive computer-based system for assisting investigators in the use of Bayesian analysis using the two parameter normal model is described. An important feature of this program is that it interacts with the investigator in the English language; he need not be familiar with computer languages or with the internal workings of the computer.…
Descriptors: Bayesian Statistics, Computer Oriented Programs, Data Analysis, Interaction
Peer reviewedKennedy, Peter – Journal of Economic Education, 1986
Concludes that for most researchers trained in classical statistics, the use of the Bayesian approach requires substantial retooling. Observes that the technical details of the Bayesian approach are formidable, and will require studying textbooks, applications, and computer packages, as well as consulting colleagues. (Author/JDH)
Descriptors: Bayesian Statistics, Data Analysis, Economic Research, Economics Education
Levy, Roy; Mislevy, Robert J. – 2003
This paper aims to describe a Bayesian approach to modeling and estimating cognitive models both in terms of statistical machinery and actual instrument development. Such a method taps the knowledge of experts to provide initial estimates for the probabilistic relationships among the variables in a multivariate latent variable model and refines…
Descriptors: Bayesian Statistics, Cognitive Processes, Markov Processes, Mathematical Models
Peer reviewedSchwartz, Steven; Dalgleish, Len – Journal of Research in Personality, 1982
Statistical significance is not a sufficient condition for claiming a hypothesis has been supported. Constructive replications are more important. Statistically significant results may be meaningless while a sequence of nonsignificant results may be quite important. Gives advice on how to overcome some limitations of classifical statistical…
Descriptors: Bayesian Statistics, Data Analysis, Personality Studies, Research Methodology
Peer reviewedChuang, David T.; And Others – Journal of Educational Statistics, 1981
Approaches to the determination of cut-scores have used threshold, normal ogive, linear and discrete utility functions. These approaches are examined by investigating conditions on the posterior, likelihood and utility functions required for setting cut-scores in a Bayesian approach. (Author/JKS)
Descriptors: Bayesian Statistics, Criterion Referenced Tests, Cutting Scores, Decision Making
Klugkist, Irene; Laudy, Olav; Hoijtink, Herbert – Psychological Methods, 2005
Researchers often have one or more theories or expectations with respect to the outcome of their empirical research. When researchers talk about the expected relations between variables if a certain theory is correct, their statements are often in terms of one or more parameters expected to be larger or smaller than one or more other parameters.…
Descriptors: Researchers, Bayesian Statistics, Mathematical Concepts, Statistical Analysis
PDF pending restorationvan der Linden, Wim J.; Eggen, Theo J. H. M. – 1986
A procedure for the sequential optimization of the calibration of an item bank is given. The procedure is based on an empirical Bayes approach to a reformulation of the Rasch model as a model for paired comparisons between the difficulties of test items in which ties are allowed to occur. First, it is indicated how a paired-comparisons design…
Descriptors: Bayesian Statistics, Foreign Countries, Item Banks, Latent Trait Theory
Sympson, James B. – 1976
Latent trait test score theory is discussed primarily in terms of Birnbaum's three-parameter logistic model, and with some reference to the Rasch model. Equations and graphic illustrations are given for item characteristic curves and item information curves. An example is given for a hypothetical 20-item adaptive test, showing cumulative results…
Descriptors: Adaptive Testing, Bayesian Statistics, Item Analysis, Latent Trait Theory
Peer reviewedAlemi, Farrokh – Evaluation Review, 1987
Trade-offs are implicit in choosing a subjective or objective method for evaluating social programs. The differences between Bayesian and traditional statistics, decision and cost-benefit analysis, and anthropological and traditional case systems illustrate trade-offs in choosing methods because of limited resources. (SLD)
Descriptors: Bayesian Statistics, Case Studies, Evaluation Methods, Program Evaluation
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

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