This paper deals with the situation where scores on a number of parallel tests are obtained for each of a set of persons, and these persons are assumed to constitute, in so far as their scores for the tests are concerned, a random sample from some population of interest. (Author)

Basic mathematical concepts of Managerial Economics, a way of quantitatively analyzing and structuring the making of a business decision, are presented. Advantages and disadvantages of its use in business are discussed and several recent applications are given. (DT)

The use of Bayesian and empirical Bayesian techniques to summarize results from parallel randomized experiments is illustrated using the results of eight such experiments from an SAT coaching study. Graphical techniques, simulation techniques, and methods for monitoring the adequacy of model specification are highlighted. (Author/JKS)

A method of identifying learning disabled adolescents using the method of Bayesian Revision of Subjective Probabilities, which utilizes both teacher judgments and psychometric tests, is proposed. (DB)

Computation and interpretation of Bayesian full-rank multivariate analysis of variance and covariance is described and illustrated in an exposition intended for readers familiar with univariate analysis of variance and multiple regression. (Author)

Explored procedures to detect test takers using item preknowledge in computerized adaptive testing and suggested a Bayesian posterior log odds ratio index for this purpose. Simulation results support the use of the odds ratio index. (SLD)

Developed Markov Chain Monte Carlo procedures to perform Bayesian inference, model checking, and model comparison in heterogeneous factor analysis. Tested the approach with synthetic data and data from a consumption emotion study involving 54 consumers. Results show that traditional psychometric methods cannot fully capture the heterogeneity in…

Studied whether ordered latent class models can be used as nonparametric item response theory (NIRT) models to scale polytomous models. Simulation findings show that the Bayesian estimation method presented can handle the inequality restrictions on the parameters and the sparseness of the data quite well. (SLD)

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)

It is shown that Bayesian algorithms are computationally simpler in frequency formats than in the probability formats used in previous research. Analysis of several thousand solutions to Bayesian problems showed that when information was presented in frequency formats, statistically naive participants derived up to 50% of inferences by Bayesian…

A proportional reduction in loss (PRL) measure for reliability of categorical data is explored for the situation in which each of "N" judges assigns a subject to one of "K" categories. Calculating a lower bound for reliability under more general conditions than had been proposed is demonstrated. (SLD)

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)

Presents a procedure, based on a Bayesian updating of the item information, for locating on the latent trait scale the scores or responses of items that follow the three-parameter logistic and monotone partial credit models. Applications are provided in terms of selecting items or score categories for criterion-referenced interpretation of mapping…

Demonstrates the use of the well-known Bayes factor in the Bayesian literature for hypothesis testing and model comparison in general two-level structural equation models. Shows that the proposed method is flexible and can be applied to situations with a wide variety of nonnested models. (SLD)

Knowledge concerning domain-specific regularities in sequential structure has long been known to affect recall for serial order. However, very little work has been done toward specifying the exact role such knowledge plays. The present article proposes a theory of serial recall in structured domains, based on Bayesian decision theory and a set of…