Examined are methodologies for modeling students' choices among higher education institutions. A statistical technique called "conditional logit analysis" is applicable to the problem studied. These applications are reviewed and certain weaknesses inherent in the approach are pointed out. Alternative approaches are offered, based on the…

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.…

A presentation of the 40-year history of psychometrics is given with comments about needed trends for the future. Computers have radically changed the time required for data processing. In testing, many promising developments, such as Kristof's reliability for vector variables, latent class and latent struction models, one-factor ration scale in…

It is shown that the common and unique variance estimates produced by a type of estimation procedure for the unrestricted common factor model have a predictable sum which is always greater than the maximum likelihood estimate of the total variance. A simple alternative method of specifying the Bayesian parameters required by the procedure is…

Item response curves for a set of binary responses are studied from a Bayesian viewpoint of estimating the item parameters. For the two-parameter logistic model with normally distributed ability, restricted bivariate beta priors are used to illustrate the computation of the posterior mode via the EM algorithm. (Author/LMO)

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)

An active area in psychometric research is coordinated task design and statistical analysis built around cognitive models. Compared with classical test theory and item response theory, there is often less information from observed data about the measurement-model parameters. On the other hand, there is more information from the grounding…

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…

To better describe individual behavior within a system, this paper uses a sample of longitudinal test scores from a large urban school system to consider hierarchical Bayes estimation of a multilevel linear regression model in which each individual regression slope of test score on time switches at some unknown point in time, "kj."…

A decision theory approach is used to model the information retrieval decision problem of which documents to retrieve from a library collection in response to a specific user query for information. Thorough discussions of decision theory and Bayesian statistics are presented. (19 references) (Author/SJ)

A Bayesian framework for making mastery/nonmastery decisions based on multivariate test data is described. Overall, mastery is granted if the posterion expected loss associated with such action is smaller than the one incurred by denying mastery. (Author/JKS)

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…

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)

A modified beta binomial model is presented for use in analyzing random guessing multiple choice tests and taste tests. Detection probabilities for each item are distributed beta across the population subjects. Properties for the observable distribution of correct responses are derived. Two concepts of true score estimates are presented.…

Bayesian techniques are adapted to the estimation of stimulus-response curves. Illustrative examples deal with estimation of person characteristic curves and item characteristic curves in the context of mental testing, and with estimation of a stimulus-response curve using data from a psychophysical experiment. (Author/JKS)