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A model for integrating fixed-, random-, and mixed-effects meta-analyses into structural equation modeling.
Abstract
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 appropriate transformation on the data, studies in a meta-analysis can be analyzed as subjects in a structural equation model. This article also highlights some practical benefits of using the SEM approach to conduct a meta-analysis. Specifically, the SEM-based meta-analysis can be used to handle missing covariates, to quantify the heterogeneity of effect sizes, and to address the heterogeneity of effect sizes with mixture models. Examples are used to illustrate the equivalence between the conventional meta-analysis and the SEM-based meta-analysis. Future directions on and issues related to the SEM-based meta-analysis are discussed.
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“To produce the main estimates, we used random-effects metaanalytic structural equation modeling, as described by Cheung (2008).”
From How Much Does Education Improve Intelligence? A Meta-Analysis (2018) · cites this paper as Cheung, 2008
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Metadata
- Authors
- Cheung, M. W.-L.
- Affiliations
- National University of Singapore (SG)
- Corresponding author
- Cheung, Mike W.-L.
- ORCID
- Cheung, Mike W.-L.
- Venue
- Psychological Methods
- Published
- 2008
- Volume
- 13
- Issue
- 3
- Pages
- 182-202
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2102695454
- Cited by
- 175
- References
- 117
- Citations by year
- 2026: 10 · 2025: 6 · 2024: 5 · 2023: 11 · 2022: 13 · 2021: 4 · 2020: 6 · 2019: 6 · 2018: 15 · 2017: 12 · 2016: 11 · 2015: 20 · 2014: 14 · 2013: 15 · 2012: 10
- FWCI
- 6.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Methods (publishedVersion)
- PubMed (publishedVersion)
- National University of Singapore (submittedVersion)
- Funders
- Ministry of Education (R-581-000-064-112)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Keywords
- structural equation modeling, fixed-effects meta-analysis, random-effects meta-analysis, effect size heterogeneity, mixture models, missing covariates, data transformation
- MeSH terms
- Humans, Models, Psychological, Meta-Analysis as Topic
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