This paper presents some Bayesian theories of simultaneous optimization of decision rules for test-based decisions. Simultaneous decision making arises when an institution has to make a series of selection, placement, or mastery decisions with respect to subjects from a population. An obvious example is the use of individualized instruction in…

A Bayesian procedure is given for estimation in unrestricted common factor analysis. A choice of the form of the prior distribution is justified. The procedure achieves its objective of avoiding inadmissible estimates of unique variances, and is reasonably insensitive to certain variations in the shape of the prior distribution. (Author/BJG)

The purpose of this study was to compare the relative classificatory ability of the Linear Discriminant Function (LDF) and the Bayesian Taxonomic Procedure (BTP) when these techniques are applied to multivariate normal and nonnormal data with differing degrees of overlap in the distributions of the predictor variables. (Editor)

The application of the Minnesota Adaptive Instructional System (MAIS) decision procedure by R. D. Tennyson et al. (1975, 1977) is examined. The MAIS is a computer-based adaptive instructional system. The problems of determining the optimal number of interrogatory examples in the MAIS can be formalized as a problem of Bayesian decision making. Two…

During the last decade the use of Bayesian statistical method has become quite prevalent in the educational community. Yet, like most statistical techniques, little has been written concerning the application of these methods to the classroom setting. The purpose of this paper is to help correct such a deficiency in the literature by developing a…

A model is proposed to explain the retrieval characteristics of an information retrieval system. (Author)

See TM 501 202-3 and EJ 060 883 for related articles. (MLP)

An alternative item-selection procedure for use with Owen's Bayesian adaptive testing strategy is proposed. This procedure is, by design, faster than Owen's original procedure because it searches only part of the total item pool. Item selections are, however, identical for both methods. After a conceptual development of the rapid-search procedure,…

The decision process required for Individually Prescribed Instruction (IPI), an adaptive instructional program developed at the University of Pittsburgh, is described. In IPI, short tests are used to determine the level of proficiency of each student in precisely defined learning objectives. The output of these tests is used to guide instructional…

The use of Bayesian statistics as the basis of classical analysis of data is described. Bayesian analysis is a set of procedures for changing opinions about a given phenomenon based upon rational observation of a set of data. The Bayesian arrives at a set of prior beliefs regarding some states of nature; he observes data in a study and then…

Bayesian statistical inference is unfamiliar to many educational evaluators. While the classical model is useful in educational research, it is not as useful in evaluation because of the need to identify solutions to practical problems based on a wide spectrum of information. The reason Bayesian analysis is effective for decision making is that it…

In this study, the graduate school admission policy at a medium-sized, state-supported university is analyzed using a combination of Bayesian and cost/benefit decision analysis techniques. (Author)

Mandatory drug testing of workers will create problems due to the low predictive ability of urinalysis. The predictive value of drug testing in populations of low drug incidence is illustrated using Bayes' Theorem. (MT)

Diagnostic hit rates for the Diagnostic Inventory of Personality and Symptoms were compared to diagnosis by psychiatrists of the same patients. The Probability Scale employing Bayesian concepts and base rates correctly classified 70% of the patients and was more accurate by far than the other two methods used. (Author/ABB)

This paper reviews various procedures for constructing an interval for an individual's true score given the assumption that errors of measurement are distributed as binomial. This paper also presents two general interval estimation procedures (i.e., normal approximation and endpoints conversion methods) for an individual's true scale score;…