When norming tests, it may be preferable to use the matrix sampling technique. The results from the samples may be used to estimate what the distribution of scores would have been if each subject had taken all the items. This paper compares four methods for making these estimates. The sample size made it possible to compare the techniques in a…

Since the primary purpose of classical testing is to rank order examinees consistently, the absolute value of the true score has been relatively unimportant. However, the major purpose of criterion referenced testing is to estimate the true capabilities of examinees to perform specific tasks. Hence, the problems of true score determination assume…

This article describes a new testing method which can be used to screen learning-deficient children fast, reliably, and inexpensively out of any population of public school systems. (Editor)

The rule space model permits measurement of cognitive skill acquisition and error diagnosis. Further discussion introduces Bayesian hypothesis testing and bug distribution. An illustration involves an artificial intelligence approach to testing fractions and arithmetic. (Author/GDC)

An approximation procedure is proposed for the posterior means and standard deviation of the ability parameter in an item response model. The method is illustrated for the two-parameter logistic model using data from a 39-item American College Testing mathematics test. The effect of sample size is considered. (SLD)

In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a time period of substantive interest relate to differences in subsequent change. This report presents a fully Bayesian approach to estimating three-level hierarchical models in which latent variable…

To reduce the cost of item writing and to enhance the flexibility of item presentation, items can be generated by item-cloning techniques. An important consequence of cloning is that it may cause variability on the item parameters. Therefore, a multilevel item response model is presented in which it is assumed that the item parameters of a…

For complex educational assessments, there is an increasing use of "item families," which are groups of related items. However, calibration or scoring for such an assessment requires fitting models that take into account the dependence structure inherent among the items that belong to the same item family. C. Glas and W. van der Linden…

Educational assessments that exploit advances in technology and cognitive psychology can produce observations and pose student models that outstrip familiar test-theoretic models and analytic methods. Bayesian inference networks (BINs), which include familiar models and techniques as special cases, can be used to manage belief about students'…

This paper discusses the Lens Model' approach to the analysis of subject performance in multiple-cue judgment tasks embedded in probabilistic environments. (Author/RK)

Describes a procedure, called a full Bayesian procedure, for making decisions in connection with criterion-referenced measurements. The procedure uses continuous utility functions instead of a dichotomized utility structure and combines the posterior distribution for a certain person with utility functions for "advance" and "retain" decisions…

The effect of performance evaluations on expectations for future performances is studied using an extension of a Bayesian model. Whereas the model was originally limited to the cases where person C is both an actor and an observer, in the present extension these become particular cases of the model. (Author/RD)

A method of item factor analysis is described, which is based on Thurstone's multiple-factor model and implemented by marginal maximum likelihood estimation and the EM algorithm. Also assessed are the statistical significance of successive factors added to the model, provisions for guessing and omitted items, and Bayes constraints. (TJH)

Previous work on the mathematical and implementation details of the marginalized maximum likelihood estimation procedure is extended to encompass the marginalized Bayesian procedure for estimating item parameters of R. J. Mislevy (1986) and to communicate this procedure to users of the BILOG computer program. (SLD)