Background: There is a diagnostic dilemma when a child presents with rib fractures after cardiopulmonary resuscitation (CPR) where child abuse is suspected as the cause of collapse. We have performed a systematic review to establish the evidence base for the following questions: (i) Does cardiopulmonary resuscitation cause rib fractures in…

This manuscript introduces a new Bayesian finite mixture methodology for the joint clustering of row and column stimuli/objects associated with two-mode asymmetric proximity, dominance, or profile data. That is, common clusters are derived which partition both the row and column stimuli/objects simultaneously into the same derived set of clusters.…

In this article, a maximum likelihood (ML) approach for analyzing a rather general two-level structural equation model is developed for hierarchically structured data that are very common in educational and/or behavioral research. The proposed two-level model can accommodate nonlinear causal relations among latent variables as well as effects…

This study introduces an order-constrained Bayes inference framework useful for analyzing data containing dichotomous scored item responses, under the assumptions of either the monotone homogeneity model or the double monotonicity model of nonparametric item response theory (NIRT). The framework involves the implementation of Gibbs sampling to…

This article examines a subscore augmentation procedure. The approach uses empirical Bayes adjustments and is intended to improve the overall accuracy of measurement when information is scant. Simulations examined the impact of the method on subscale scores in a variety of realistic conditions. The authors focused on two popular scoring methods:…

Using detailed administrative data for the public K-12 schools of North Carolina, we measure racial segregation in its public schools. With data for the 2005-2006 school year, we update previously published calculations that measure segregation by unevenness in racial enrollment patterns, both between schools and within schools. We find that…

Over the course of instruction, instructors generally collect a great deal of information about each student. Integrating that information intelligently requires models for how a student's proficiency changes over time. Armed with such models, instructors can "filter" the data--more accurately estimate the student's current proficiency…

The accuracy of the Markov Chain Monte Carlo (MCMC) procedure Gibbs sampling was considered for estimation of item parameters of the two-parameter logistic model. Data for the Law School Admission Test (LSAT) Section 6 were analyzed to illustrate the MCMC procedure. In addition, simulated data sets were analyzed using the MCMC, marginal Bayesian…

A Bayesian procedure to estimate the three-parameter normal ogive model and a generalization to a model with multidimensional ability parameters are discussed. The procedure is a generalization of a procedure by J. Albert (1992) for estimating the two-parameter normal ogive model. The procedure will support multiple samples from multiple…

A version of sequential mastery testing is studied in which response behavior is modeled by an item response theory (IRT) model. First, a general theoretical framework is sketched that is based on a combination of Bayesian sequential decision theory and item response theory. A discussion follows on how IRT based sequential mastery testing can be…

The empirical Bayes modeling approach--latent ability random sampling in the item response theory (IRT) context--to the IRT modeling of psychological tests is described. Under the usual empirical Bayes unidimensional IRT modeling approach, the posterior distribution of examinee ability given test response is approximately normal for a long test.…

This study investigates attributions based on behavior congruent with situational demands (in-role) and those based on behavior incongruent with situational demands (out-of-role). (Editor)

In clinical trials, adaptive allocation means that the therapies assigned to the next patient or patients depend on the results obtained thus far in the trial. Although many adaptive allocation procedures have been proposed for clinical trials, few have actually used adaptive assignment, largely because classical frequentist measures of inference…

We investigated the properties of the distribution of human solution times for Traveling Salesperson Problems (TSPs) with increasing numbers of nodes. New experimental data are presented that measure solution times for carefully chosen representative problems with 10, 20, . . . 120 nodes. We compared the solution times predicted by the convex hull…

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…