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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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Carmen Köhler; Lale Khorramdel; Artur Pokropek; Johannes Hartig – Journal of Educational Measurement, 2024
For assessment scales applied to different groups (e.g., students from different states; patients in different countries), multigroup differential item functioning (MG-DIF) needs to be evaluated in order to ensure that respondents with the same trait level but from different groups have equal response probabilities on a particular item. The…
Descriptors: Measures (Individuals), Test Bias, Models, Item Response Theory
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Maria Vrikki; Leonidas Kyriakides; Andria Dimosthenous – Educational Research and Evaluation, 2024
The paper investigates the potential of using international large-scale assessment studies for conducting follow-up studies testing models of educational effectiveness. The impact of teacher factors coming from the "dynamic model of educational effectiveness" and the "dialogic education theory" on student literacy achievement…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, International Assessment
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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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Zhou, Hao; Ma, Xin – Sociological Methods & Research, 2023
Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe…
Descriptors: Simulation, Hierarchical Linear Modeling, Socioeconomic Status, Institutional Characteristics
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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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Tang, Shifang; Wang, Zhuoying; Sutton-Jones, Kara L. – Educational Studies, 2023
We examined student reading achievement in rural and non-rural school districts in Texas. Our research questions probed the improvement in student performance over time, differences in the number of students achieving at different performance levels, and the impact of district-level characteristics on reading achievement. Through quantitative…
Descriptors: Hierarchical Linear Modeling, Elementary School Students, Achievement Tests, Reading Tests
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Wang, Faming; Wang, Yehui; Liu, Yaping; Leung, Shing On – Scandinavian Journal of Educational Research, 2023
The importance of the opportunity to learn (OTL) for mathematics achievement has been extensively researched. However, there were still unanswered questions regarding OTL's measurement, analytical level, and relationship with motivational beliefs. To fill in the gaps, we aimed to (1) scrutinize the reliability and validity of OTL, (2) investigate…
Descriptors: International Assessment, Foreign Countries, Achievement Tests, Secondary School Students
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Courtney, Matthew; Karakus, Mehmet; Ersozlu, Zara; Nurumov, Kaidar – Large-scale Assessments in Education, 2022
This study analyzed the latest four PISA surveys, 2009, 2012, 2015, and 2018, to explore the association between students' ICT-related use and math and science performance. Using ICT Engagement Theory as a theoretical framework and a three-level hierarchical linear modeling approach, while controlling for confounding effects, ICT-related…
Descriptors: Technology Uses in Education, Student Attitudes, Mathematics Achievement, Science Achievement
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Lyu, Weicong; Kim, Jee-Seon; Suk, Youmi – Journal of Educational and Behavioral Statistics, 2023
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…
Descriptors: Hierarchical Linear Modeling, Bayesian Statistics, Causal Models, Statistical Inference
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Pongsophon, Pongprapan – Science Education International, 2023
This study examined the factors that determined the science achievement of fourth-grade students on the Trends in International Mathematics and Science Study (TIMSS) 2019 in the USA. The data were retrieved from the TIMSS international database and imported to the R program for manipulation. The EdSurvey package was used to conduct multilevel…
Descriptors: Hierarchical Linear Modeling, Predictor Variables, Science Achievement, Elementary School Students
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Chine, Danielle R.; Larwin, Karen H. – International Journal of Research in Education and Science, 2022
Hierarchical linear modeling (HLM) has become an increasingly popular multilevel method of analyzing data among nested datasets, in particular, the effect of specialized academic programming within schools. The purpose of this methodological study is to demonstrate the use of HLM to determine the effectiveness of STEM programming in an Ohio middle…
Descriptors: Middle Schools, STEM Education, Instructional Effectiveness, Program Development
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Qian, Quan; Lau, Kit-ling – Journal of Research in Reading, 2022
Background: Research has shown that achievement goals and reading instruction play important roles in students' reading performance. However, little is known about the specific effects of different types of achievement goals and reading instructional practices on reading performance in mainland China. Methods: This study used Programme of…
Descriptors: Achievement Gains, School Districts, Teaching Methods, Reading Achievement
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Guo, Qing; Qiao, CuiLan; Ibrahim, Bashirah – Journal of Science Education and Technology, 2022
Information and communication technology (ICT) is key to educational development. This study explores the mechanism influencing the use of ICT on students' science literacy. We utilized two-level hierarchical linear models and structural equation models to analyze data collected from the 2015 Program for International Student Assessment (PISA) in…
Descriptors: Correlation, Scientific Literacy, Information Technology, Personal Autonomy