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Julia-Kim Walther; Martin Hecht; Steffen Zitzmann – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Small sample sizes pose a severe threat to convergence and accuracy of between-group level parameter estimates in multilevel structural equation modeling (SEM). However, in certain situations, such as pilot studies or when populations are inherently small, increasing samples sizes is not feasible. As a remedy, we propose a two-stage regularized…
Descriptors: Sample Size, Hierarchical Linear Modeling, Structural Equation Models, Matrices
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Mingya Huang; David Kaplan – Journal of Educational and Behavioral Statistics, 2025
The issue of model uncertainty has been gaining interest in education and the social sciences community over the years, and the dominant methods for handling model uncertainty are based on Bayesian inference, particularly, Bayesian model averaging. However, Bayesian model averaging assumes that the true data-generating model is within the…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Statistical Inference, Predictor Variables
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Shu-Hao Wu; Morris Siu-Yung Jong; Chin-Chung Tsai – Education and Information Technologies, 2025
Spherical video-based virtual reality (SVVR) offers teachers an accessible means to use virtual reality. However, research into the effects of learning materials in teacher-developed SVVR activities on student learning remains limited. This study recruited 33 elementary school teachers and the 841 students in their classes. This study classified…
Descriptors: Learner Engagement, Hierarchical Linear Modeling, Computer Simulation, Technology Uses in Education