An approach is presented to simultaneously optimize decision rules for combinations of elementary decisions through a framework derived from Bayesian decision theory. The developed linear utility model for selection-mastery decisions was applied to a sample of 43 first year medical students to illustrate the procedure. (SLD)

The concept of consensus ordering is defined, and formulas for exact and approximate posterior probabilities for consensus ordering are developed under the assumption of a generalized Mallows' model with a diffuse conjugate prior. These methods are applied to a data set concerning 98 college students. (SLD)

If overattribution--the tendency for observers to think actors' attitudes match their behaviors even when behaviors are not freely performed--results from the fundamental attribution error, then observers must believe the coerced behavior is attributionally informative. This assumption was tested by (1) investigating the extent to which attitude…

A Bayesian solution is suggested to the problem of jointly estimating "k is greater than 1" binomial parameters in conjunction with the problem of testing, in a Bayesian sense, the hypothesis "H" of parametric homogeneity. Applications of the estimates are illustrated with several types of data, including ophthalmological…

The use of subjective probability as a theoretical model for enrollment forecasting is proposed, and the results of an application of subjective probability to enrollment forecasting at the University of Toledo are reported. Subjective probability can be used as an enrollment forecasting technique for both headcount and full-time equivalent using…

A general approach is proposed for modeling the structure of a two-way contingency table, and for drawing inferences about the marginal and interaction effects, cell parameters, and conditional probabilities. The prior distribution expresses uncertainty in a simple reduced model, in particular the independence model. The posterior estimates of the…

Advantages and disadvantages of joint maximum likelihood, marginal maximum likelihood, and Bayesian methods of parameter estimation in item response theory are discussed and compared. (Author)

The decision making processes of children in a probabilistic environment were studied within the context of the theory of signal detection (TSD). The relationship between the age of the child and his ability to revise decision criteria was examined, as well as the appropriateness of TSD measures and methodology with children. It was hypothesized…

The reliability of four branching algorithms commonly used in computer adaptive testing (CAT) was examined. These algorithms were: (1) maximum likelihood (MLE); (2) Bayesian; (3) modal Bayesian; and (4) crossover. Sixty-eight undergraduate college students were randomly assigned to one of the four conditions using the HyperCard-based CAT program,…

Classical statistical methods and the small enrollments in graduate departments have constrained the Graduate Record Examinations (GRE) Validity Study Service to providing only validities for single predictors. Estimates of the validity of two or more predictors, used jointly, are considered too unreliable because the corresponding prediction…

The conventional method of measuring ability--based on items with assumed true parameter values obtained from a pretest--is compared to a Bayesian method that deals with the uncertainties of such items. Data from a 1987 American College Testing Program mathematics test indicate that maximum likelihood/Bayesian techniques underestimate uncertainty.…

Methods for predicting specific college course grades, based on small numbers of observations, were investigated. These methods use collateral information across potentially diverse institutions to obtain refined within-group parameter estimates. One method, referred to as pooled least squares with adjusted intercepts, assumes that slopes and…

A study was conducted to compare tailored testing procedures based on a Bayesian ability estimation technique and on a maximum likelihood ability estimation technique. The Bayesian tailored testing procedure selected items so as to minimize the posterior variance of the ability estimate distribution, while the maximum likelihood tailored testing…

The problems associated with misclassifying students when pass-fail decisions are based on test scores are discussed. One protection against misclassification is to set a confidence interval around the cutting score. Those whose scores fall above the interval are passed; those whose scores fall below the interval are failed; and those whose scores…

Two methods of using collateral information from similar institutions to predict college freshman grade average were investigated. One central prediction model, referred to as pooled least squares with adjusted intercepts, assumes that slopes and residual variances are homogeneous across selected colleges. The second model, referred to as Bayesian…