The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with…

Causal learning requires integrating constraints provided by domain-specific theories with domain-general statistical learning. In order to investigate the interaction between these factors, the authors presented preschoolers with stories pitting their existing theories against statistical evidence. Each child heard 2 stories in which 2 candidate…

Data from three studies were used to investigate whether the establishment of a no-smoking agreement is related to lower odds of adolescent smoking. The prevalence of a no-smoking agreement was first explored by using a national sample involving 4,501 Dutch adolescents. Second, data from a longitudinal study among 595 early adolescents and their…

Effective literacy teachers share a variety of instructional traits such as the ability to kidwatch, pedagogically reflect, and make informed decisions based on ill-structured and complex data. Teacher educators face the challenge of helping preservice teachers develop such traits so as to prepare them to be successful literacy teachers. One…

Purpose: The purpose of this research is twofold. The first purpose is to utilize a new methodology (Bayesian networks) for aggregating various quality indicators to measure the overall quality of care in nursing homes. The second is to provide new insight into the relationships that exist among various measures of quality and how such measures…

In tests with time limits, items at the end are often not reached. Usually, the pattern of missing responses depends on the ability level of the respondents; therefore, missing data are not ignorable in statistical inference. This study models data using a combination of two item response theory (IRT) models: one for the observed response data and…

Despite having drawn from empirical evidence and cumulative prior expertise in the formulation of research questions as well as study design, each study is treated as a stand-alone product rather than positioned within a sequence of cumulative evidence. While results of prior studies are typically cited within the body of prior literature review,…

In this essay, the author tries to look forward into the 21st century to divine three things: (i) What skills will researchers in the future need to solve the most pressing problems? (ii) What are some of the most likely candidates to be those problems? and (iii) What are some current areas of research that seem mined out and should not distract…

The threshold utility model for culture-fair selection is defined for both quota-free and for restricted selection. In addition a full Bayesian solution based on posterior predictive distributions is provided. Mathematical derivations and an example are provided. (JKS)

Proposes a Bayesian analysis of the multivariate linear model with polytomous variables. Shows how a Gibbs sampler algorithm is implemented to produce the Bayesian estimates. Illustrates the proposed methodology through examples using multivariate linear regression and multivariate two-way analysis of variance with real data. (SLD)

Studied a multiple group model with ordinal categorical observed variables that are manifestations of underlying normal variables. Proposed to apply across-group stochastic constraints on thresholds to identify the model and used a Bayesian approach to analyze the model. Simulation findings and the analysis of a real data set show the usefulness…

Illustrates procedures for prediction analysis in 2 X 2 contingency tables through the analyses of solutions of six types of problems associated with the acquisition of fractions. Reviews and extends confidence interval procedures previously proposed for an index of predictive efficiency of implication hypotheses. Compares frequentist coverage…

Presents a Bayesian method for obtaining an interval estimate of the population squared multiple correlation from an incomplete multivariate normal data set. Estimates were constructed using Gibbs sampling. Simulation studies indicate that the method can yield accurate interval estimates of the population squared multiple correlation. (SLD)

Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…

This article presents relevant research on Bayesian methods and their major applications to modeling in an effort to lay out differences between the frequentist and Bayesian paradigms and to look at the practical implications of these differences. Before research is reviewed, basic tenets and methods of the Bayesian approach to modeling are…