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Daniel Kasper; Katrin Schulz-Heidorf; Knut Schwippert – Sociological Methods & Research, 2024
In this article, we extend Liao's test for across-group comparisons of the fixed effects from the generalized linear model to the fixed and random effects of the generalized linear mixed model (GLMM). Using as our basis the Wald statistic, we developed an asymptotic test statistic for across-group comparisons of these effects. The test can be…
Descriptors: Models, Achievement Tests, Foreign Countries, International Assessment
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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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Yamaguchi, Kazuhiro – Journal of Educational and Behavioral Statistics, 2023
Understanding whether or not different types of students master various attributes can aid future learning remediation. In this study, two-level diagnostic classification models (DCMs) were developed to represent the probabilistic relationship between external latent classes and attribute mastery patterns. Furthermore, variational Bayesian (VB)…
Descriptors: Bayesian Statistics, Classification, Statistical Inference, Sampling
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Suk, Youmi; Kim, Jee-Seon; Kang, Hyunseung – Journal of Educational and Behavioral Statistics, 2021
There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…
Descriptors: Artificial Intelligence, Statistical Analysis, Statistical Inference, Classification
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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2021
Large-scale assessments (LSAs) use Mislevy's "plausible value" (PV) approach to relate student proficiency to noncognitive variables administered in a background questionnaire. This method requires background variables to be completely observed, a requirement that is seldom fulfilled. In this article, we evaluate and compare the…
Descriptors: Data Analysis, Error of Measurement, Research Problems, Statistical Inference
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Alkhateeb, Mohammad Ahmad – International Journal of Instruction, 2019
The aim of this study was to investigate the extent of embodying thinking levels in the eighth-grade textbook and teachers' classroom questions and exams. Five teachers who teach eighth grade were chosen from schools that obtained the highest and lowest TIMSS results in Zarqa City, Jordan. Textbook content analysis, teachers' classroom observation…
Descriptors: Foreign Countries, Grade 8, Textbooks, Textbook Content
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Rutkowski, David; Delandshere, Ginette – Large-scale Assessments in Education, 2016
To answer the calls for stronger evidence by the policy community, educational researchers and their associated organizations increasingly demand more studies that can yield causal inferences. International large scale assessments (ILSAs) have been targeted as a rich data sources for causal research. It is in this context that we take up a…
Descriptors: Inferences, Educational Research, Attribution Theory, Educational Policy
Stapleton, Laura M.; Kang, Yoonjeong – Sociological Methods & Research, 2018
This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to…
Descriptors: Probability, Hierarchical Linear Modeling, Sampling, Inferences
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Nixon, Ryan S.; Barth, Katie N. – School Science and Mathematics, 2014
The results of international assessments such as the Trends in International Mathematics and Science Study (TIMSS) are often reported as rankings of nations. Focusing solely on national rank can result in invalid inferences about the relative quality of educational systems that can, in turn, lead to negative consequences for teachers and students.…
Descriptors: Comparative Analysis, Test Items, Data Analysis, Inferences
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Li, Wei; Konstantopoulos, Spyros – Journal of Research on Educational Effectiveness, 2016
Class size reduction policies have been widely implemented around the world in recent years. However, findings about the effects of class size on student achievement have been mixed. This study examines class size effects on fourth-grade mathematics achievement in 14 European countries using data from TIMSS (Trends in International Mathematics and…
Descriptors: Class Size, Grade 4, Mathematics Achievement, Evidence
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Skaggs, Gary; Wilkins, Jesse L. M.; Hein, Serge F. – International Journal of Testing, 2016
The purpose of this study was to explore the degree of grain size of the attributes and the sample sizes that can support accurate parameter recovery with the General Diagnostic Model (GDM) for a large-scale international assessment. In this resampling study, bootstrap samples were obtained from the 2003 Grade 8 TIMSS in Mathematics at varying…
Descriptors: Achievement Tests, Foreign Countries, Elementary Secondary Education, Science Achievement
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Brown, Margaret – Curriculum Journal, 2011
Inferences from recent international comparative data on mathematical attainment, frequently quoted as justification for curriculum change, are critically examined, and the implications are contrasted with expressed curricular aims. Using characterisations by Ball (1990) and Ernest (1991), positions of key actors are analysed in relation to…
Descriptors: National Curriculum, Mathematics Curriculum, Curriculum Development, Cultural Background