A marginal maximum a posteriori (MMAP) procedure was implemented to estimate item parameters in the generalized graded unfolding model (GGUM). Estimates from the MMAP method were compared with those derived from marginal maximum likelihood (MML) and Markov chain Monte Carlo (MCMC) procedures in a recovery simulation that varied sample size,…

In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we motivate…

This dissertation reports the results of three studies and a pilot study. The first study was a Monte Carlo validation study that examined the accuracy of a new visual inspection method, the semi-interquartile range method. Results of the study indicated that this method had lower levels of power than a previously validated method, the…

In the current study we investigate whether 2- and 3-year-old German children use intonation productively to mark the informational status of referents. Using a story-telling task, we compared children's and adults' intonational realization via pitch accent (H*, L* and de-accentuation) of New, Given, and Contrastive referents. Both children and…

This study investigates procedures for controlling the familywise error rate (FWR) when testing hypotheses about multiple, correlated outcome variables in repeated measures (RM) designs. A content analysis of RM research articles published in 4 psychology journals revealed that 3 quarters of studies tested hypotheses about 2 or more outcome…

This article presents a new method to detect copying on a standardized multiple-choice exam. The method combines two statistical approaches in successive stages. The first stage uses Kullback-Leibler divergence to identify examinees, called subjects, who have demonstrated inconsistent performance during an exam. For each subject the second stage…

There are several important decisions that must be made when implementing taxometric procedures such as mean above minus below a cut (MAMBAC), maximum covariance (MAXCOV), and maximum eigenvalue (MAXEIG). A Monte Carlo study was performed with 10,000 (5,000 categorical, 5,000 dimensional) samples to examine 5 ways to locate the first and last…

Online forums (synchronous and asynchronous) offer exciting data opportunities to analyze how people influence one another through their interactions. However, researchers must address several analytic difficulties involving the data (missing values, nested structure [messages within topics], non-sequential messages), outcome variables (discrete…

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are…

Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…

If single-case experimental designs are to be used to establish guidelines for evidence-based interventions in clinical and educational settings, numerical values that reflect treatment effect sizes are required. The present study compares four recently developed procedures for quantifying the magnitude of intervention effect using data with known…

Developmental science is replete with studies on the impact of mothers on their children, but little is known about what might best help caregivers to function well themselves. In an initial effort to address this gap, we conducted an Internet-based study of over 2,000 mostly well-educated mothers, seeking to illuminate salient risk and protective…

Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

Hierarchical Linear Modeling (HLM) sample size recommendations are mostly made with traditional group-design research in mind, as HLM as been used almost exclusively in group-design studies. Single-case research can benefit from utilizing hierarchical linear growth modeling, but sample size recommendations for growth modeling with HLM are scarce…