The theory of signal detection is convenient for measuring mnemonic ability in recognition memory paradigms. In these paradigms, randomly selected participants are asked to study randomly selected items. In practice, researchers aggregate data across items or participants or both. The signal detection model is nonlinear; consequently, analysis…

In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of…

Explores the robustness of conclusions from a statistical model against variations in model choice with an illustration from G. Box and G. Tiao (1973). Suggests that simultaneous consideration of a class of models for the same data is sometimes superior to analyzing the data under one model and demonstrates advantages to Adaptive Bayesian…

A scheme is described for locally Bayesian parameter updating in models structured as successions of component functions. The essential idea is to back-propagate the target data to interior modules, such that an interior component's target is the input to the next component that maximizes the probability of the next component's target. Each layer…

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks…

The DA-T Gibbs sampler is proposed by Maris and Maris (2002) as a Bayesian estimation method for a wide variety of "Item Response Theory (IRT) models". The present paper provides an expository account of the DA-T Gibbs sampler for the 2PL model. However, the scope is not limited to the 2PL model. It is demonstrated how the DA-T Gibbs…

Practical meta-analysis of correlation matrices generally ignores covariances (and hence correlations) between correlation estimates. The authors consider various methods for allowing for covariances, including generalized least squares, maximum marginal likelihood, and Bayesian approaches, illustrated using a 6-dimensional response in a series of…

Presents a Bayesian approach to the evaluation of person fit in item response theory (IRT) models. Works the procedure in detail for the three parameter normal ogive model, but shows that the procedure can be generalized to many other IRT models. (SLD)

Fully and partially ranked data arise in a variety of contexts. From a Bayesian perspective, attention has focused on distance-based models; in particular, the Mallows model and extensions thereof. In this paper, a class of prior distributions, the "Binary Tree," is developed on the symmetric group. The attractive features of the class are: it…

Two needs of Georgia State University Professional Development School Partnerships are to show increases in both student academic achievement and teacher efficacy. The Teacher-Intern-Professor (TIP) Model was designed to address these needs. The TIP model focuses on using the university and school partnership to support Georgia State University…

It is commonly proposed that educational and psychological assessments consist of a multifaceted procedure that incorporates scores from a variety of tests and resources. Little guidance has been offered regarding the method for selecting a combination of testing instruments used in an evaluation. The problem of test selection is discussed in the…

Experimental data on human reasoning in hypothesis-testing tasks is reassessed in light of a Bayesian model of optimal data selection in inductive hypothesis testing. The rational analysis provided by the model suggests that reasoning in such tasks may be rational rather than subject to systematic bias. (SLD)

Students are characterized by different learning styles, focusing on different types of information and processing this information in different ways. One of the desirable characteristics of a Web-based education system is that all the students can learn despite their different learning styles. To achieve this goal we have to detect how students…

The purpose of this study is to examine the effects of a false assumption regarding the motivation of examinees on test construction. Simulated data were generated using two models of item responses (the three-parameter logistic item response model alone and in combination with Wise's examinee persistence model) and were calibrated using a…

This study analyses the relationship between subjective and objective measures of well-being in selected European countries using the data of the European Community Household Panel (ECHP). In the first part of the paper, we develop a random-effect ordered probit model, separately for each country, relating the subjective measure of income…