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Meta-analytic structural equation modeling: A two-stage approach.
Abstract
To synthesize studies that use structural equation modeling (SEM), researchers usually use Pearson correlations (univariate r), Fisher z scores (univariate z), or generalized least squares (GLS) to combine the correlation matrices. The pooled correlation matrix is then analyzed by the use of SEM. Questionable inferences may occur for these ad hoc procedures. A 2-stage structural equation modeling (TSSEM) method is proposed to incorporate meta-analytic techniques and SEM into a unified framework. Simulation results reveal that the univariate-r, univariate-z, and TSSEM methods perform well in testing the homogeneity of correlation matrices and estimating the pooled correlation matrix. When fitting SEM, only TSSEM works well. The GLS method performed poorly in small to medium samples.
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“…to methods focused on contrasting and combining outcomes of various studies, in the hope of measuring patterns among study results, sources of divergence among those results, and other interesting relationships that may come to light in the perspective of multiple studies (Cheung and Chan 2005).”
BackgroundMethod
Metadata
- Authors
- Cheung, M. W.-L., & Chan, W.
- Venue
- Psychological Methods
- Published
- 2005-03
- Volume
- 10
- Issue
- 1
- Pages
- 40-64
- ISSN
- 1082-989X (ISSN-L)
- 1939-1463
- OpenAlex
- W2021670737
- Cited by
- 637
- References
- 13
- FWCI
- 8.85
- Type
- journal article
- Language
- en
- Open access
- closed
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