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Examining Second Language Listening and Metacognitive Awareness: A Meta-Analytic Structural Equation Modeling Approach
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In'nami, Yo; Cheung, Mike W.-L.; Koizumi, Rie; Wallace, Matthew P. – Language Learning, 2023
Second language (L2) listening comprehension is a function of many variables. We focused on metacognitive awareness, which we measured using the Metacognitive Awareness Listening Questionnaire (MALQ; Vandergrift et al., 2006), and meta-analyzed (a) the factor structure of the MALQ and (b) the relationship between metacognitive awareness and L2…
Descriptors: Second Language Learning, Listening Comprehension, Metacognition, Meta Analysis
Meta-Analytic Structural Equation Modeling Made Easy: A Tutorial and Web Application for One-Stage MASEM
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Jak, Suzanne; Li, Hongli; Kolbe, Laura; Jonge, Hannelies; Cheung, Mike W.-L. – Research Synthesis Methods, 2021
Meta-analytic structural equation modeling (MASEM) refers to fitting structural equation models (SEMs) (such as path models or factor models) to meta-analytic data. Currently, fitting MASEMs may be challenging for researchers that are not accustomed to working with R software and packages. Therefore, we developed webMASEM; a web application for…
Descriptors: Meta Analysis, Structural Equation Models, Tutorial Programs, Computer Oriented Programs
Some Reflections on Combining Meta-Analysis and Structural Equation Modeling
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Cheung, Mike W.-L. – Research Synthesis Methods, 2019
Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…
Descriptors: Structural Equation Models, Meta Analysis, Statistical Analysis, Data Analysis
Random-Effects Models for Meta-Analytic Structural Equation Modeling: Review, Issues, and Illustrations
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Cheung, Mike W.-L.; Cheung, Shu Fai – Research Synthesis Methods, 2016
Meta-analytic structural equation modeling (MASEM) combines the techniques of meta-analysis and structural equation modeling for the purpose of synthesizing correlation or covariance matrices and fitting structural equation models on the pooled correlation or covariance matrix. Both fixed-effects and random-effects models can be defined in MASEM.…
Descriptors: Statistical Analysis, Models, Meta Analysis, Structural Equation Models
A Model for Integrating Fixed-, Random-, and Mixed-Effects Meta-Analyses into Structural Equation Modeling
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Cheung, Mike W.-L. – Psychological Methods, 2008
Meta-analysis and structural equation modeling (SEM) are two important statistical methods in the behavioral, social, and medical sciences. They are generally treated as two unrelated topics in the literature. The present article proposes a model to integrate fixed-, random-, and mixed-effects meta-analyses into the SEM framework. By applying an…
Descriptors: Structural Equation Models, Effect Size, Meta Analysis, Models
Classifying Correlation Matrices into Relatively Homogeneous Subgroups: A Cluster Analytic Approach
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Cheung, Mike W.-L.; Chan, Wai – Educational and Psychological Measurement, 2005
Researchers are becoming interested in combining meta-analytic techniques and structural equation modeling to test theoretical models from a pool of studies. Most existing procedures are based on the assumption that all correlation matrices are homogeneous. Few studies have addressed what the next step should be when studies being analyzed are…
Descriptors: Multivariate Analysis, Meta Analysis, Correlation, Structural Equation Models