This study explores three understudied facets--quadratic effects, change over time, and gender as a moderator--of the otherwise well-documented relationships between statistics anxiety and academic performance. Using pre- and post- course survey data among a sample of 111 undergraduate students in Social Statistics courses at a U.S. Midwestern…

When analyzing large-scale assessments (LSAs) that use complex sampling designs, it is important to account for probability sampling using weights. However, the use of these weights in multilevel models has been widely debated, particularly regarding their application at different levels of the model. Yet, no consensus has been reached on the best…

This paper examines whether parental engagement in early childhood and preschooling act as substitutes, or whether their joint effect enhances students' learning outcomes. We utilize the TIMSS 2019 dataset and employ a hierarchical linear modeling (HLM) approach to analyze data from 52 countries, ensuring a robust examination of cross-national…

This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…

This study used a propensity score approach to estimate treatment effects in a multilevel setting. The propensity score approach involves the estimation of propensity scores for covariate balancing and the estimation of treatment effects. This study aimed at understanding how propensity scores estimated through a simple logistic regression compare…

Student motivation predicts academic achievement, engagement, and related academic behaviors. Yet in spite of the importance of motivation for academic success, few studies have examined the school and national-level contextual characteristics associated with motivation. The present study uses hierarchical linear modeling to analyze a large…

This study examined the effect of similar vs. dissimilar proficiency distributions on uniform DIF detection on a statewide eighth grade mathematics assessment. Results from the similar- and dissimilar-ability reference groups with an SWD focal group were compared for four models: logistic regression, hierarchical generalized linear model (HGLM),…

The purpose of this evaluation was to examine the impact of i-Ready Personalized Instruction that met Curriculum Associates' recommended usage levels on mathematics achievement, as measured by the Massachusetts Comprehensive Assessment System (MCAS) mathematics assessment. This study compared mathematics achievement growth of students who used…

Effect size reporting is crucial for interpretation of applied research results and for conducting meta-analysis. However, clear guidelines for reporting effect size in multilevel models have not been provided. This report suggests and demonstrates appropriate effect size measures including the ICC for random effects and standardized regression…

This longitudinal study examined the influence of prekindergarten teacher characteristics and classroom instructional processes during mathematical activities on the growth of mathematics learning scores in prekindergarten, kindergarten, and first grade. Participants attended state-funded and Head Start prekindergarten programs. Mathematical…

The author examined the simultaneous influence of Japanese middle school student and school socioeconomic status (SES) on student math achievement with two-level multilevel analysis models by utilizing the Trends in International Mathematics and Science Study (TIMSS) Japan data sets. The theoretical framework used in this study was…

Computer adaptive tests (CATs) hold promise to monitor student progress within multitiered systems of support. However, the relationship between how long and how often data are collected and the technical adequacy of growth estimates from CATs has not been explored. Given CAT administration times, it is important to identify optimal data…

The purpose of this paper is to demonstrate Hispanic students' mathematics achievement growth rate in Inclusive science, technology, engineering, and mathematics (STEM) high schools compared to Hispanic students' mathematics achievement growth rate in traditional public schools. Twenty-eight schools, 14 of which were Texas STEM (T-STEM) academies…

This study examined the relationship between the American College Testing (ACT) college mathematics readiness standard and college mathematics achievement using a sample of students who met or exceeded the minimum 3 years high school mathematics coursework recommended by ACT. According to ACT, a student who scores 22 or higher on the ACT…

By using multi-level modeling, this study explores the impact of students' perception of the quality of the teacher-student relationship and family structure on student achievement after controlling for socioeconomic status (SES), school urbanicity, and school control. The data from 750 schools and 17,000 10th grade students were analyzed. Family…