Stan is a new Bayesian statistical software program that implements the powerful and efficient Hamiltonian Monte Carlo (HMC) algorithm. To date there is not a source that systematically provides Stan code for various item response theory (IRT) models. This article provides Stan code for three representative IRT models, including the…

The present article considers a fundamental question in evaluation research: "By how much do program effects vary across sites?" The article first presents a theoretical model of cross-site impact variation and a related estimation model with a random treatment coefficient and fixed site-specific intercepts. This approach eliminates…

The use of some very simple loss or utility functions in educational evaluation has recently been advocated by Gross and Su, Petersen and Novick, and Petersen. This paper demonstrates that more realistic utility functions can easily be used and may be preferable in some applications. (Author/CTM)

The purpose of this paper is to demonstrate in detail how the Empirical Bayes (EB) statistical estimation strategy can be applied to an important class of educational research contexts. EB methods are tailored specifically to the analysis of data with a hierarchical structure. For instance, investigators may be interested in discovering how…

In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)

Vector sum of a white noise in an unknown hyperspace and an Ornstein-Uhlenbeck process in an unknown line is observed through sharp linear test functions over a finite time span. Parameters associated with white noise are determinable and index measure-equivalence classes in relevant sample space. Intraclass relative density provides a basis for…

Estimation theory in educational statistics and the application of hierarchical linear models are reviewed. Observations within each group vary as a function of microparameters. Microparameters vary across the population of groups as a function of macroparameters. Bayes and empirical Bayes viewpoints review examples with two levels of hierarchy.…

The scientific implications and practical applications of the Stein estimator approach for estimating true scores from observed scores are of potentially great importance. The conceptual complexity is not much greater than that required for more conventional regression models. The empirical Bayesian aspect allows the examiner to incorporate…

This paper aims to describe a Bayesian approach to modeling and estimating cognitive models both in terms of statistical machinery and actual instrument development. Such a method taps the knowledge of experts to provide initial estimates for the probabilistic relationships among the variables in a multivariate latent variable model and refines…

Approaches to the determination of cut-scores have used threshold, normal ogive, linear and discrete utility functions. These approaches are examined by investigating conditions on the posterior, likelihood and utility functions required for setting cut-scores in a Bayesian approach. (Author/JKS)

A procedure for the sequential optimization of the calibration of an item bank is given. The procedure is based on an empirical Bayes approach to a reformulation of the Rasch model as a model for paired comparisons between the difficulties of test items in which ties are allowed to occur. First, it is indicated how a paired-comparisons design…

Latent trait test score theory is discussed primarily in terms of Birnbaum's three-parameter logistic model, and with some reference to the Rasch model. Equations and graphic illustrations are given for item characteristic curves and item information curves. An example is given for a hypothetical 20-item adaptive test, showing cumulative results…

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…