Background: Researchers are often interested in testing the effectiveness of an intervention on multiple outcomes, for multiple subgroups, at multiple points in time, or across multiple treatment groups. The resulting multiplicity of statistical hypothesis tests can lead to spurious findings of effects. Multiple testing procedures (MTPs)…

Background: Standard methods for analysing data from large-scale assessments (LSA) cannot merely be adopted if hierarchical (or multilevel) regression modelling should be applied. Currently various approaches exist; they all follow generally a design-based model of estimation using the pseudo maximum likelihood method and adjusted weights for the…

This report presents the statistical theory underlying the "RCT-YES" software that estimates and reports impacts for RCTs for a wide range of designs used in social policy research. The report discusses a unified, non-parametric design-based approach for impact estimation using the building blocks of the Neyman-Rubin-Holland causal…

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

The random-threshold generalized unfolding model (RTGUM) was developed by treating the thresholds in the generalized unfolding model as random effects rather than fixed effects to account for the subjective nature of the selection of categories in Likert items. The parameters of the new model can be estimated with the JAGS (Just Another Gibbs…

In some tests, examinees are required to choose a fixed number of items from a set of given items to answer. This practice creates a challenge to standard item response models, because more capable examinees may have an advantage by making wiser choices. In this study, we developed a new class of item response models to account for the choice…

Analysis of ordered binary and unordered binary data has received considerable attention in social and psychological research. This article introduces a Bayesian approach, which has several nice features in practical applications, for analyzing nonlinear structural equation models with dichotomous data. We demonstrate how to use the software…

Different random or purposive allocations of items to parcels within a single sample are thought not to alter structural parameter estimates as long as items are unidimensional and congeneric. If, additionally, numbers of items per parcel and parcels per factor are held fixed across allocations, different allocations of items to parcels within a…

The process-component approach has become quite popular for examining many psychological concepts. A typical example is the model with internal restrictions on item difficulty (MIRID) described by Butter (1994) and Butter, De Boeck, and Verhelst (1998). This study proposes a hierarchical generalized random-situation random-weight MIRID. The…

Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…

Contemporary teaching and learning approaches expect students--at any level of education--to be active producers of knowledge. This leads to the need for creation of instructional strategies, learning environments and tasks that can offer students opportunities for active learning. Research argues that one of the most meaningful and engaging forms…

Longitudinal data describe developmental patterns and enable predictions of individual changes beyond sampled time points. Major methodological issues in longitudinal data include modeling random effects, subject effects, growth curve parameters, and autoregressive residuals. This study embedded the longitudinal model within a multigroup…

In this study, all the advantages of slope parameters, random weights, and latent regression are acknowledged when dealing with component and composite items by adding slope parameters and random weights into the standard item response model with internal restrictions on item difficulty and formulating this new model within a multilevel framework…

Three decision consistency and accuracy (DC/DA) methods, the Livingston and Lewis (LL) method, LEE method, and the Hambleton and Han (HH) method, were evaluated. The purposes of the study were: (1) to evaluate the accuracy and robustness of these methods, especially when their assumptions were not well satisfied, (2) to investigate the "true"…

An overview of a course on modeling and simulation offered at the Nanotechnology Engineering undergraduate program at the University of Waterloo. The motivation for having this course in the undergraduate nanotechnology curriculum, the course structure, and its learning objectives are discussed. Further, one of the computational laboratories…