Background: Power analyses for a cluster-randomized trial (CRT) require estimates of additional design parameters beyond those needed for an individually randomized trial. In a 2-level CRT, there are two sample sizes, the number of clusters and the number of individuals per cluster. The intraclass correlation (ICC), or the proportion of variance…

Simulation studies are the basic tools of quantitative methodologists used to obtain empirical solutions to statistical problems that may be impossible to derive through direct mathematical computations. The successful execution of many simulation studies relies on the accurate generation of correlated multivariate data that adhere to a particular…

Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and inaccessible for evaluation or modification by researchers and practitioners, limiting their accountability and ethical design. Moreover, predictive models are often opaque…

Based on a brief analysis of the current situation of university education management and research on intelligent algorithms, this article constructs a university education management system based on big data. For the clustering and prediction modules in higher education management, corresponding algorithms are used for optimization design. A…

In this article, I present a new multivariate regression model for analyzing outcomes with network dependence. The model is capable to account for two types of outcome dependence including the mean dependence that allows the outcome to depend on selected features of a known dependence network and the error dependence that allows the outcome to be…

The presence of clustered data is common in the sociobehavioral sciences. One approach that specifically deals with clustered data but has seen little use in education is the generalized estimating equations (GEEs) approach. We provide a background on GEEs, discuss why it is appropriate for the analysis of clustered data, and provide worked…

The purpose of the current paper is to provide a step-by-step tutorial for employing the list experiment to control for Social Desirability Bias (SDB). Sport management scholars routinely rely on self-report data in cross-sectional settings to test research hypotheses. However, concerns exist regarding the use of self-reports without adjusting for…

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…

When randomized control trials are not possible, quasi-experimental methods often represent the gold standard. One quasi-experimental method is difference-in-difference (DiD), which compares changes in outcomes before and after treatment across groups to estimate a causal effect. DiD researchers often use fairly exhaustive robustness checks to…

This article presents a novel approach to introducing principal component analysis (PCA), using summary tables and descriptive statistics. Given its applicability across a variety of academic disciplines, this topic offers abundant opportunity for class discussion and activities. However, teaching PCA in an introductory class can be challenging…

Although many textbooks on multivariate statistics discuss the common factor analysis model, few of these books mention the problem of factor score indeterminacy (FSI). Thus, many students and contemporary researchers are unaware of an important fact. Namely, for any common factor model with known (or estimated) model parameters, infinite sets of…

Binary outcomes are often analyzed in cluster randomized trials (CRTs) using logistic regression and cluster robust standard errors (CRSEs) are routinely used to account for the dependent nature of nested data in such models. However, CRSEs can be problematic when the number of clusters is low (e.g., < 50) and, with CRTs, a low number of…

Numerous activities and measures can be observed in the context of digitization. However, these are often not interrelated or sufficiently anchored institutionally and structurally with regard to overarching goals. The aim of this study is therefore to carry out a theory-based clustering of connotations with the concept of digit(al)ization in…

Validity of performance standards is a key element for the defensibility of standard setting results, and validating performance standards requires collecting multiple pieces of evidence at every step during the standard setting process. This study employs a statistical procedure, latent class analysis, to set performance standards and compares…

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…