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Choi, Kilchan; Kim, Jinok – Journal of Educational and Behavioral Statistics, 2019
This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of…
Descriptors: Regression (Statistics), Hierarchical Linear Modeling, Longitudinal Studies, Cohort Analysis
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Ker, Hsiang-Wei – Asia Pacific Journal of Education, 2017
Motivational constructs and students' engagements have great impacts on students' mathematics achievements, yet they have not been theoretically investigated using international large-scale assessment data. This study utilized the mathematics data of the Trends in International Mathematics and Science Study 2011 to conduct a comparative and…
Descriptors: Mathematics Achievement, Comparative Analysis, Achievement Tests, Elementary Secondary Education
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Warne, Russell T. – Gifted Child Quarterly, 2014
Above-level testing is the practice of administering aptitude or academic achievement tests that are designed for typical students in higher grades or older age-groups to gifted or high-achieving students. Although widely accepted in gifted education, above-level testing has not been subject to careful psychometric scrutiny. In this study, I…
Descriptors: Academically Gifted, Middle School Students, Longitudinal Studies, Hierarchical Linear Modeling