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Tenko Raykov; Ahmed Haddadi; Christine DiStefano; Mohammed Alqabbaa – Educational and Psychological Measurement, 2025
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…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Educational Research, Statistical Inference
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Chunhua Cao; Yan Wang; Eunsook Kim – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Multilevel factor mixture modeling (FMM) is a hybrid of multilevel confirmatory factor analysis (CFA) and multilevel latent class analysis (LCA). It allows researchers to examine population heterogeneity at the within level, between level, or both levels. This tutorial focuses on explicating the model specification of multilevel FMM that considers…
Descriptors: Hierarchical Linear Modeling, Factor Analysis, Nonparametric Statistics, Statistical Analysis
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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
Alex Gibson; Paul Bywaters; John Stephenson; Jude Ranasinghe – UK Department for Education, 2025
LG Futures, The University of Huddersfield and the University of Plymouth were commissioned by the Ministry of Housing, Communities and Local Government (MHCLG) and the Department for Education (DfE) to develop a new model to show relative need to spend on Children and Young People's Services across local authorities in England. This formed part…
Descriptors: Foreign Countries, Social Services, Children, Funding Formulas
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Bruno Arpino; Silvia Bacci; Leonardo Grilli; Raffaele Guetto; Carla Rampichini – Evaluation Review, 2025
We consider estimating the effect of a treatment on a given outcome measured on subjects tested both before and after treatment assignment in observational studies. A vast literature compares the competing approaches of modelling the post-test score conditionally on the pre-test score versus modelling the difference, namely, the gain score. Our…
Descriptors: Scores, Pretesting, Conditioning, Achievement Gains
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Yasuhiro Yamamoto; Yasuo Miyazaki – Journal of Experimental Education, 2025
Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian…
Descriptors: Sample Size, Hierarchical Linear Modeling, Bayesian Statistics, Prior Learning
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Tong Wu; Stella Y. Kim; Carl Westine; Michelle Boyer – Journal of Educational Measurement, 2025
While significant attention has been given to test equating to ensure score comparability, limited research has explored equating methods for rater-mediated assessments, where human raters inherently introduce error. If not properly addressed, these errors can undermine score interchangeability and test validity. This study proposes an equating…
Descriptors: Item Response Theory, Evaluators, Error of Measurement, Test Validity
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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
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Umut Atasever; Francis L. Huang; Leslie Rutkowski – Large-scale Assessments in Education, 2025
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…
Descriptors: Mathematics Tests, International Assessment, Elementary Secondary Education, Foreign Countries
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Stephen M. Leach; Jason C. Immekus; Jeffrey C. Valentine; Prathiba Batley; Dena Dossett; Tamara Lewis; Thomas Reece – Assessment for Effective Intervention, 2025
Educators commonly use school climate survey scores to inform and evaluate interventions for equitably improving learning and reducing educational disparities. Unfortunately, validity evidence to support these (and other) score uses often falls short. In response, Whitehouse et al. proposed a collaborative, two-part validity testing framework for…
Descriptors: School Surveys, Measurement, Hierarchical Linear Modeling, Educational Environment
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Aditi Bhutoria; Nayyaf Aljabri; Saheli Bose – International Journal of Child Care and Education Policy, 2025
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…
Descriptors: Early Childhood Education, Parenting Skills, Child Rearing, Preschool Children
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F. Sehkar Fayda-Kinik; Munevver Cetin – Journal of Computer Assisted Learning, 2025
Background: The unprecedented access to information in the 21st century entails a deep understanding of information and communication technology (ICT)-related factors in education and their impacts on learning and teaching. The role of attitudes towards ICT is a proven factor in student achievement. However, there is no consensus about the…
Descriptors: Information Technology, Technology Uses in Education, Academic Achievement, Secondary Education