The goal of this work is to provide instructors with detailed information about their classes at each assignment during the term. The information is both on an individual level and at the aggregate level. We used the large number of grades, which are available online these days, along with data-mining techniques to build our models. This enabled…

Bayesian techniques were developed for approximating the joint and marginal distributions of universe scores in single-facit-mixed-model designs with unknown covariance structure. Empirical results indicate that when compared with Cronbach's estimates, marginal means obtained through this procedure are substantially better predictors of subsequent…

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…

Discusses , in the context of confirmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Uses a small simulation study to show that in this context, Bayes factors and the pseudo likelihood ratio statistics have the best properties. (SLD)

A probabilistic model for interactive retrieval is presented. Bayesian statistical decision theory principles are applied: use of prior and sample information about the relationship of document descriptions to query relevance; maximization of expected value of a utility function, to the problem of optimally restructuring search strategies in an…

Nonlinear latent variable models are specified that include quadratic forms and interactions of latent regressor variable as special cases. To estimate the parameters, the models are put in a Bayesian framework with conjugate priors for the parameters. The proposed estimation methods are illustrated by two simulation studies. (SLD)

The standard statistical analysis of data classified in two ways (say into rows and columns) is through an analysis of variance that splits the total variation of the data into the main effect of rows, the main effect of columns, and the interaction between rows and columns. This paper presents an alternative Bayesian analysis of the same…

The use of some very simple loss or utility functions in educational evaluation has recently been advocated by Gross and Su, Petersen and Novick, and Petersen. This paper demonstrates that more realistic utility functions can easily be used and may be preferable in some applications. (Author/CTM)

This study investigated statistical methods for identifying errors in Bayesian networks (BN) with latent variables, as found in intelligent cognitive assessments. BN, commonly used in artificial intelligence systems, are promising mechanisms for scoring constructed-response examinations. The success of an intelligent assessment or tutoring system…

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.…

The purpose of this paper is to demonstrate in detail how the Empirical Bayes (EB) statistical estimation strategy can be applied to an important class of educational research contexts. EB methods are tailored specifically to the analysis of data with a hierarchical structure. For instance, investigators may be interested in discovering how…

Bayesian analysis of an m-group model is considered. A convenient stage III prior is proposed, and cases when the posterior distributions take on a simple form are exhibited. The behavior of various point estimators of the linear parameters of the model are explored in a Monte Carlo study. In the simple model considered, the O'Hagan estimator…

A research project developed a computer program for analyzing time series quasi-experimental data. The program generates a nonstationary, integrated moving average time series model; it is used to estimate a parameter which indexes the instantaneous change in level of the time series due to a predesignated treatment. The entire method is based on…

Techniques are developed for constructing confidence regions for each of the points in a multidimensional scaling solution. Bayesian credibility regions are discussed, and a technique for displaying these regions is described. (Author/JKS)