A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization to a model with multidimensional ability parameters are discussed. The procedure is a generalization of a procedure by J. Albert (1992) for estimating the two-parameter normal ogive model. The procedure will support multiple samples from multiple…

A version of sequential mastery testing is studied in which response behavior is modeled by an item response theory (IRT) model. First, a general theoretical framework is sketched that is based on a combination of Bayesian sequential decision theory and item response theory. A discussion follows on how IRT based sequential mastery testing can be…

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.…

This study investigates attributions based on behavior congruent with situational demands (in-role) and those based on behavior incongruent with situational demands (out-of-role). (Editor)

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…

The scientific implications and practical applications of the Stein estimator approach for estimating true scores from observed scores are of potentially great importance. The conceptual complexity is not much greater than that required for more conventional regression models. The empirical Bayesian aspect allows the examiner to incorporate…

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."…