This paper investigates methods that avoid using multiple groups to represent the missing data patterns in covariance structure modeling, attempting instead to do a single-group analysis where the only action the analyst has to take is to indicate that data is missing. A new covariance structure approach developed by B. Muthen and G. Arminger is…

Forty subjects were trained to make numerical predictions of a criterion from a cue. (Editor)

A coherent system of decision making is described that may be incorporated into an instructional sequence to provide a supplement to the experience-based judgment of the classroom teacher. The elements of this decision process incorporate prior information such as a teacher's past experience, experimental results such as a test score, and…

One of six summaries of workshop sessions (See TM 000 130), designed to strengthen the evaluation of costly programs and their effects, this handbook presents an analysis of both random and nonrandom sampling errors by application of the Bayesian model. This model attempts to formalize the process and procedures of inference from data through…

Recently the application of Bayesian statistical procedures within the field of guidance and counseling has been receiving attention. This paper justifies and illustrates a simple, direct application of Bayes' Formula to expectancy tables. To make the application a counselor must specify prior probabilities that a student will attain success…

A numerical procedure is outlined for obtaining an interval estimate of true score. The procedure is applied to several sets of test data. (Author)

Several Bayesian approaches to the simultaneous estimation of the means of k binomial populations are discussed. This has particular applicability to criterion-referenced or mastery testing. (Author/JKS)

Describes a method of dealing with partially-responded-to questionnaires in survey research which utilizes nonparametric Bayesian discriminant analysis to predict missing responses based on "profiles" of the partial and the "complete" respondents. Some background of nonresponse bias in survey research is discussed, and two other methods of dealing…

This article explores the potential of Bayesian inference as a theoretical framework for describing how people evaluate hypotheses. First, it identifies a set of logically possible forms of non-Bayesian behavior. Second, it reviews existing research in a variety of areas to see whether these possibilities are ever realized. (Author/BW)

In comparing student ratings of teaching performance, instructor evaluations at the beginning of the course are needed. Without such prior information, student assessment of teachers at the end of the course may not be valid. (Author/RM)

A structural multilevel model is presented in which some of the variables cannot be observed directly but are measured using tests or questionnaires. Observed dichotomous or ordinal politicos response data serve to measure the latent variables using an item response theory model. The latent variables can be defined at any level of the multilevel…

In some areas of measurement item parameters should not be modeled as fixed but as random. Examples of such areas are: item sampling, computerized item generation, measurement with substantial estimation error in the item parameter estimates, and grouping of items under a common stimulus or in a common context. A hierarchical version of the…

This study investigated the applicability to computerized adaptive testing (CAT) data of a differential item functioning (DIF) analysis that involves an empirical Bayes (EB) enhancement of the popular Mantel Haenszel (MH) DIF analysis method. The computerized Law School Admission Test (LSAT) assumed for this study was similar to that currently…

This examination of data selection preceding multivariate analysis compares results grained with "gentle" and "draconian" variable elimination. To acquire comparable results, two stages of statistical exploration into an integrated model of motivation, learning strategies, and quality of teaching were used. The goal of the…

The accuracy of Gibbs sampling, a Markov chain Monte Carlo procedure, was considered for estimation of item and ability parameters under the two-parameter logistic model. Memory test data were analyzed to illustrate the Gibbs sampling procedure. Simulated data sets were analyzed using Gibbs sampling and the marginal Bayesian method. The marginal…