This note is concerned with the study of temporal development in several indices reflecting clustering effects in multilevel designs that are frequently utilized in educational and behavioral research. A latent variable method-based approach is outlined, which can be used to point and interval estimate the growth or decline in important functions…

Mediation analyses are crucial for understanding the mechanisms through which interventions or theoretical constructs influence outcomes within nested structures, commonly found in education, psychology, and sociology. Recognizing the importance of these effects, designing and analyzing robust studies to detect them is essential. This dissertation…

The paper has three major objectives. The first objective of the paper is to synthesize and define common categories of meta-analysis. The second objective is to propose a way to comprehend these common categories of meta-analysis through learning from their respective generic conceptual frameworks. The third objective is to point out which R…

Meta-analyses of educational research findings frequently involve statistically dependent effect size estimates. Meta-analysts have often addressed dependence issues using ad hoc approaches that involve modifying the data to conform to the assumptions of models for independent effect size estimates, such as by aggregating estimates to obtain one…

The "k"-means clustering method, while widely embraced in college student typology research, is often misunderstood and misapplied. Many researchers regard "k"-means as a near-universal solution for uncovering homogeneous student groups, believing its success hinges primarily on the selection of an appropriate "k."…

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…

Meta-analytic studies of second language (L2) learning typically employ a classic approach to meta-analysis. Although the classic approach can clarify findings, a multivariate, multilevel meta-analysis (3M) approach increases transparency by accounting for (a) dependencies in the evidence presented by primary studies, (b) methodological…

Engagement has been recognized as one of the most important factors of learning and achievement in academic settings. Research on engagement has been gearing toward a "person-in-context" orientation, where both personal characteristics and contextual features in relation to students' engagement are considered. This orientation allows a…

This research aims to propose a bibliometric map of studies on the use of STEM in education. This study used publication co-citation analysis, author co-citation analysis, and word frequency analysis methods to reveal the structure and transformation of STEM literature. Descriptive data such as the distribution of studies in the field by country,…

Coping with evolution and the changes it brings to the workplace remains a major concern for organizational leaders. This study explores the hotspots, trends, and future directions of the field of organizational unlearning to complement the extant research. A bibliometric analysis based on the literature collected by the Web of Science database…

The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all units within the group are exposed to the treatment. However, the treatment is non-randomly assigned. COSs are common in both education and health services research. In…

Mixture modeling is a latent variable (i.e., a variable that cannot be measured directly) approach to quantitatively represent unobserved subpopulations within an overall population. It includes a range of cross-sectional (such as latent class [LCA] or latent profile analysis) and longitudinal (such as latent transition analysis) analyses and is…

Introduction: The What Works Clearinghouse (WWC) reviews rigorous research on educational interventions with a goal of identifying "what works" and making that information accessible to educators and policymakers. The WWC has historically prioritized internal validity over external validity in rating the quality of research. One critique…

Although educational research and evaluation generally occur in multilevel settings, many analyses ignore cluster effects. Neglecting the nature of data from educational settings, especially in non-randomized experiments, can result in biased estimates with long-term consequences. Our manuscript improves the availability and understanding 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…