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Yu, Philip L. H. – Psychometrika, 2000
Studied the order-statistics models, extending the usual normal order-statistics model into one in which the underlying random variables followed a multivariate normal distribution. Used a Bayesian approach and the Gibbs sampling technique. Applied the proposed method to analyze presidential election data from the American Psychological…
Descriptors: Bayesian Statistics, Mathematical Models

Fornell, Claes; Rust, Roland T. – Psychometrika, 1989
A Bayesian approach to the testing of competing covariance structures is developed. Approximate posterior probabilities are easily obtained from the chi square values and other known constants. The approach is illustrated using an example that demonstrates how the prior probabilities can alter results concerning the preferred model specification.…
Descriptors: Bayesian Statistics, Chi Square, Comparative Analysis, Mathematical Models

Laird, Nan M.; Louis, Thomas A. – Journal of Educational Statistics, 1989
Based on the Gaussian model, methods for using measurements that depend on the true attribute to compute rankings are proposed and compared. Measurements based on an empirical Bayes model produce estimates that differ from ranking observed data. Ranking methods are illustrated with school achievement data. (TJH)
Descriptors: Bayesian Statistics, Class Rank, Mathematical Formulas, Mathematical Models
Berry, Donald A. – 1989
The use of a Bayesian approach in evaluating data from clinical trials with many treatment centers and from many studies is discussed. The main distinction between a metaanalysis and an analysis of a multicenter trial is that different studies may have very different designs, while the centers in a multicenter trial usually follow the same…
Descriptors: Bayesian Statistics, Drug Use, Mathematical Models, Meta Analysis

Raudenbush, Stephen W. – Journal of Educational Statistics, 1988
Estimation theory in educational statistics and the application of hierarchical linear models are reviewed. Observations within each group vary as a function of microparameters. Microparameters vary across the population of groups as a function of macroparameters. Bayes and empirical Bayes viewpoints review examples with two levels of hierarchy.…
Descriptors: Bayesian Statistics, Educational Research, Equations (Mathematics), Estimation (Mathematics)

Vos, Hans J. – Journal of Educational Statistics, 1990
An approach is presented to simultaneously optimize decision rules for combinations of elementary decisions through a framework derived from Bayesian decision theory. The developed linear utility model for selection-mastery decisions was applied to a sample of 43 first year medical students to illustrate the procedure. (SLD)
Descriptors: Bayesian Statistics, Decision Making, Equations (Mathematics), Higher Education

Jones, W. Paul – Educational and Psychological Measurement, 1991
A Bayesian alternative to interpretations based on classical reliability theory is presented. Procedures are detailed for calculation of a posterior score and credible interval with joint consideration of item sample and occasion error. (Author/SLD)
Descriptors: Bayesian Statistics, Equations (Mathematics), Mathematical Models, Statistical Inference

Baker, Frank B. – Applied Psychological Measurement, 1990
The equating of results from the PC-BILOG computer program to an underlying metric was studied through simulation when a two-parameter item response theory model was used. Results are discussed in terms of the identification problem and implications for test equating. (SLD)
Descriptors: Bayesian Statistics, Computer Simulation, Equated Scores, Item Response Theory

Fligner, Michael A.; Verducci, Joseph S. – Psychometrika, 1990
The concept of consensus ordering is defined, and formulas for exact and approximate posterior probabilities for consensus ordering are developed under the assumption of a generalized Mallows' model with a diffuse conjugate prior. These methods are applied to a data set concerning 98 college students. (SLD)
Descriptors: Bayesian Statistics, College Students, Equations (Mathematics), Estimation (Mathematics)

Jannarone, Robert J.; And Others – Psychometrika, 1990
A Bayes estimation procedure for Rasch-type model estimation that has statistical and computational advantages over existing methods is described. It involves constructing posterior distributions based on sample data and artificial data reflecting prior information. Its use for some Rasch-type cases, and how it can improve parameter estimation are…
Descriptors: Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics), Item Response Theory

Meredith, William; Millsap, Roger E. – Psychometrika, 1992
A unified treatment is presented for conditions that should allow detection of measurement bias using statistical procedures involving only observed or manifest variables. Computational results demonstrate that methods for studying bias that rely exclusively on manifest variables are not generally diagnostic of the presence or absence of…
Descriptors: Bayesian Statistics, Equations (Mathematics), Identification, Item Bias
Chang, Hua-Hua; Stout, William – 1991
The empirical Bayes modeling approach--latent ability random sampling in the item response theory (IRT) context--to the IRT modeling of psychological tests is described. Under the usual empirical Bayes unidimensional IRT modeling approach, the posterior distribution of examinee ability given test response is approximately normal for a long test.…
Descriptors: Ability, Bayesian Statistics, Equations (Mathematics), Item Response Theory
Berry, Donald A. – 1990
In clinical trials, adaptive allocation means that the therapies assigned to the next patient or patients depend on the results obtained thus far in the trial. Although many adaptive allocation procedures have been proposed for clinical trials, few have actually used adaptive assignment, largely because classical frequentist measures of inference…
Descriptors: Bayesian Statistics, Mathematical Models, Patients, Research Methodology

Chuang, 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

Anderson, John R. – Psychological Review, 1991
A rational model of human categorization behavior is presented that assumes that categorization reflects the derivation of optimal estimates of the probability of unseen features of objects. A case is made that categorization behavior can be predicted from the structure of the environment. (SLD)
Descriptors: Adjustment (to Environment), Bayesian Statistics, Behavior Patterns, Classification