(See also TM 501 087, TM 501 089 and TM 501 090.)

This paper develops theory and methods for the application of the Bayesian Model II method to the estimation of binomial proportions and demonstrates its application to educational data. (Author/RK)

Five impediments to accurate clinical judgment are discussed: inability to assess covariation, influence of preconceived notions, lack of awareness of one's judgmental processes, overconfidence, and hindsight bias. Presents three strategies to minimize impediments' effects: considera- tion of alternative outcomes, increased attention to data, and…

Evaluation is discussed as an information-gathering process. Currently popular evaluation programs are reviewed in relation to decision making and various approaches that seem to contribute to the decision utility of evaluation (e.g. classical approaches, Bayesian approaches, adaptive designs, and model-based evaluations) are described. (Author/AL)

Methods are described for obtaining upper and lower bounds to both false-positive and false-negative decisions with a mastery test. These methods make no assumptions about the form of the true score distribution. (CTM)

This paper argues that statistical inference practices in both educational and psychological research should be directed away from traditional significance tests in favor of Bayesian inferential methods. Regular use of exploratory data analytic methods is recommended in conjunction with computer intensive resampling methods. Approaches to…

Some alternative criteria for item selection in adaptive testing are proposed that take into account uncertainty in the ability estimates. A simulation study shows that the likelihood weighted information criterion is a good alternative to the maximum information criterion. Another good alternative uses a Bayesian expected a posteriori estimator.…

Two simple empirical approximate Bayes estimators are introduced for estimating domain scores under binomial and hypergeometric distributions respectively. Criteria are established regarding use of these functions over maximum likelihood estimation counterparts. (SLD)

Coping style and effects of counseling intervention on pain tolerance was studied for 61 elementary school students through immersion of hands in cold water. Bayesian predictive inference tools are able to distinguish between subject characteristics and manipulable treatments. Sensitivity analysis strengthens the certainty of conclusions about…

Several models of information integration are developed and analyzed in the context of a prototypical pattern-recognition task. Evaluation, integration, and decision-making processes are specified for each. Simulations and predictions are carried out to provide a measure of identifiability or extent to which they can be distinguished from one…

An extension is described to a product-testing model to account for misinformation among subjects that would lead them to perform incorrectly on "pick one of two" tests. The model is applied to a data set of 367 subjects picking 1 of 2 colas. Misinformation does exist. (SLD)

The asymptotic posterior normality of latent variable distributions is established under very general and appropriate hypotheses, providing a probabilistic basis for assessing ability estimation/prediction accuracy in the long test case, as well as a first step in making the Dutch Identity conjecture rigorous. (SLD)

Investigated model for reducing time for administration of Myers-Briggs Type Indicator (MBTI) using real-data simulation of Bayesian scaling in computerized adaptive administration. Findings from simulation study using data from 127 undergraduates are strongly supportive of use of Bayesian scaled computerized adaptive administration of MBTI.…

The precision of the group-based item-response theory (IRT) model applied to school ability estimation is described, assuming use of Bayesian estimation with precision represented by the standard deviation of the posterior distribution. Similarities with and differences between the school-based model and the individual-level IRT are explored. (SLD)

A Bayesian approach to sensitivity of inferences to possible outliers involves recalculating marginal posterior distributions of parameters of interest under assumptions of heavy tails. This strategy is implemented in the hierarchical model setting through Gibbs sampling, a Monte Carlo technique, and illustrated through a reanalysis of data on…