Evaluated with 25 learning disabled (LD) and 25 non LD elementary level children was the Bayesian method to screen children for possible LD, an approach which uses the aggregation of data--objective test scores related to likelihood ratios and a known prior odds ratio. (Author/DB)

Bayesian network models offer a large degree of flexibility for modeling dependence among observables (item outcome variables) from the same task that may be dependent. This paper explores four design patterns for modeling locally dependent observations from the same task: (1) No context--Ignore dependence among observables; (2) Compensatory…

Three separate papers are included in this report. The first describes a two-stage procedure for choosing from among several instructional programs the one which maximizes the probability of passing the test. The second gives the exact sample sizes required to determine whether a squared multiple correlation coefficient is above or below a known…

A summary of the technical problems encountered in performing Bayesian m group regression is given. Grade-point averages for students entering a vocational-technical program are predicted using ability assessments from the Career Planning Profile (CPP), a development of The American College Testing Program (ACT). The theory derived by Lindley (see…

The development of an index reflecting the probability that the observed correspondence between multiple choice test responses of two examinees was due to chance in the absence of copying was previously reported. The present paper reports the implementation of a statistic requiring less restrictive underlying assumptions but more computation time…

This article compares three models that have been the foundation for approaches to the analysis of statistical significance in early childhood research--the Fisherian and the Neyman-Pearson models (both considered "classical" approaches), and the Bayesian model. The article concludes that all three models have a place in the analysis of research…

The classification problem in educational testing is a decision problem. One must assign subjects to one of several available treatments on the basis of test scores, where the success of each treatment is measured by a different criterion. Examples of classification decisions include individualized instruction, counseling, and clinical settings.…

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 system of computer-assisted data analysis (CADA) was developed at the University of Iowa to handle the mechanical, arithmetical and computational tasks associated with Bayesian statistical analysis. The original programs were subsequently expanded and a CADA monitor constructed to aid their use; a search was then undertaken to find a means of…

An experimental study of the efficiency of human information processing is based on the Bayesian model for simple hypothesis testing with fixed binomial sampling. Each of 60 subjects is analyzed with separate ANOVAs focusing on two efficiency variables. Sample size and critical value are also analyzed. Subjects show very different utilization of…

The Libby-Novick class of three-parameter generalized beta distributions is shown to provide a rich class of prior distributions for the binomial model that removes some restrictions of the standard beta class. A numerical example indicates the desirability of using these wider classes of densities for binomial models. (Author/BW)

(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)

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…