Causal mediation analysis is a popular approach for investigating whether the effect of an exposure on an outcome is through a mediator to better understand the underlying causal mechanism. In recent literature, mediation analysis with multiple mediators has been proposed for continuous and dichotomous outcomes. In contrast, methods for mediation…

The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…

Teachers need instructionally useful data to make timely and appropriate decisions to meet their students with intensive needs (Filderman et al., 2019). Teachers have still experienced difficulty in instructional decision making in response to students' CBM data (Gesel et al., 2021). This is because data itself that was used for simply determining…

Meta-regression analyses usually focus on estimating and testing differences in average effect sizes between individual levels of each meta-regression covariate in turn. These metrics are useful but have limitations: they consider each covariate individually, rather than in combination, and they characterize only the mean of a potentially…

For assessments that use different forms in different administrations, equating methods are applied to ensure comparability of scores over time. Ideally, a score scale is well maintained throughout the life of a testing program. In reality, instability of a score scale can result from a variety of causes, some are expected while others may be…

We have expanded Stein's "Sweetness of Aspartame" laboratory project (Stein, P. J. "J. Chem. Educ." 1997, 74, 1112, DOI: 10.1021/ed074p1112) to include extensive use of statistical testing. Students test the statistical significance of a nonzero intercept in a linear regression, bias in comparison to a true value, and…

In this study, we applied elastic-net logistic regression to explore critical predictors of students' mathematics and science levels using data from eighth-grade students in the 2019 Trends in International Mathematics and Science Study (TIMSS). The elastic-net approach, a machine learning based approach combining Ridge and Least Absolute…

This Case Study explores the application of importance-performance analysis (IPA) integrated with strengths, weaknesses, opportunities, and threats (SWOT) analysis to develop strategic plans in universities. The IPA-SWOT methodology measures student satisfaction to prioritize areas for improvement, combining logistic regression analysis to assess…

Background/Context: The application of statistical modeling techniques to high-dimensional educational data presents methodological challenges, particularly the study of student transfer between higher education institutions. Over 13% of new college students each year are transfer students (National Student Clearinghouse Research Center, 2025) and…

This study explores how blended classroom teaching (the integration of online courses with face-to-face instructions) equalizes educational outcomes across regions. We point out that besides the medium function, ICT can also transmit educational resources across regions, and the resource transmission function facilitates the equalization of…

The main objective of this article is to use the logistic regression model as one of the generalized linear models to determine some factors that influence academic tripping at the University of Tabuk. In this case, student status (tripped, non-tripped) is considered as a binary variable. The data of this article were collected using a survey…

Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…

This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To…

Purpose: This article provides a tutorial introduction to ordinal pattern analysis, a statistical analysis method designed to quantify the extent to which hypotheses of relative change across experimental conditions match observed data at the level of individuals. This method may be a useful addition to familiar parametric statistical methods…

As data have become more prevalent in academia, industry, and daily life, it is imperative that undergraduate students are equipped with the skills needed to analyze data in the modern environment. In recent years there has been a lot of work innovating introductory statistics courses and developing introductory data science courses; however,…