Cluster-randomized trials have been widely used to evaluate the treatment effects of interventions on student outcomes. When interventions are implemented by teachers, researchers need to account for the nested structure in schools (i.e., students are nested within teachers nested within schools). Schools usually have a very limited number of…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Multilevel models are an increasingly popular method to analyze data that originate from a clustered or hierarchical structure. To effectively utilize multilevel models, one must have an adequately large number of clusters; otherwise, some model parameters will be estimated with bias. The goals for this paper are to (1) raise awareness of the…

To further understand the properties of data-generation algorithms for multivariate, nonnormal data, two Monte Carlo simulation studies comparing the Vale and Maurelli method and the Headrick fifth-order polynomial method were implemented. Combinations of skewness and kurtosis found in four published articles were run and attention was…

Growth mixture modeling has gained much attention in applied and methodological social science research recently, but the selection of the number of latent classes for such models remains a challenging issue, especially when the assumption of proper model specification is violated. The current simulation study compared the performance of a linear…

This study employed a quasi-experimental design to test the effects of three pedagogies on learning outcomes in a simulated psychology of gender lecture. Results showed that meaning and relational pedagogies, as well as a combination of meaning, relational, and explanatory pedagogies, significantly improved participant learning beyond self-study…

Meta-analyses often include studies that report multiple effect sizes based on a common pool of subjects or that report effect sizes from several samples that were treated with very similar research protocols. The inclusion of such studies introduces dependence among the effect size estimates. When the number of studies is large, robust variance…

In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

This study examined the effectiveness of a brief theory-based intervention on muscular strength among adolescents in a physical education setting. The intervention adopted a process-based mental simulation technique. The self-reported frequency of practising for and actual levels of abdominal muscular strength/endurance as one component of…

It is known that interventions are hard to assign randomly to subjects in social psychological studies, because randomized control is difficult to implement strictly and precisely. Thus, in nonexperimental studies and observational studies, controlling the impact of covariates on the dependent variables and addressing the robustness of the…

DIMPACK Version 1.0 for assessing test dimensionality based on a nonparametric conditional covariance approach is reviewed. This software was originally distributed by Assessment Systems Corporation and now can be freely accessed online. The software consists of Windows-based interfaces of three components: DIMTEST, DETECT, and CCPROX/HAC, which…

When randomized experiments cannot be conducted in practice, propensity score (PS) techniques for matching treated and control units are frequently used for estimating causal treatment effects from observational data. Despite the popularity of PS techniques, they are not yet well studied for matching multilevel data where selection into treatment…

A recurring theme in the literature is that simulation is a positive teaching strategy when compared to other methods of instruction and produces positive student outcomes (Jefferies, 2016). Simulation provides educators a way to reproduce a clinical teaching experience in a safe, supportive learning environment. The purpose of this quantitative…

The Current study investigated the effect of the 5E learning cycle in which the simulations were integrated on pre-service science teachers' achievement in photoelectric subject. Four sophomore level classes with their 140 students participated in the research and a quasi-experimental design was used. The classes were randomly assigned into one of…

In this article, a 2-way multigroup common factor model (MG-CFM) is presented. The MG-CFM can be used to estimate interaction effects between 2 grouping variables on 1 or more hypothesized latent variables. For testing the significance of such interactions, a likelihood ratio test is presented. In a simulation study, the robustness of the…