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Related Experiment Videos

Meta-analytic structural equation modeling: a two-stage approach.

Mike W-L Cheung1, Wai Chan2

  • 1Department of Psychology, University of Hong Kong.

Psychological Methods
|April 7, 2005
PubMed
Summary
This summary is machine-generated.

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See all related articles

Researchers often combine correlation matrices using methods like Pearson correlations or Fisher z scores for structural equation modeling (SEM). A new two-stage SEM (TSSEM) method integrates meta-analysis and SEM, showing superior performance in fitting SEM models.

Area of Science:

  • Psychometrics
  • Quantitative Psychology
  • Statistical Modeling

Background:

  • Synthesizing research using structural equation modeling (SEM) often involves combining correlation matrices.
  • Common methods include Pearson correlations (univariate r), Fisher z scores (univariate z), or generalized least squares (GLS).
  • These traditional approaches can lead to questionable inferences when analyzing pooled correlation matrices with SEM.

Purpose of the Study:

  • To propose a novel two-stage structural equation modeling (TSSEM) method.
  • To integrate meta-analytic techniques with SEM within a unified framework.
  • To evaluate the performance of TSSEM against existing methods for synthesizing correlation matrices.

Main Methods:

  • The study proposed a two-stage structural equation modeling (TSSEM) approach.

Related Experiment Videos

  • Simulation studies were conducted to compare TSSEM with univariate-r, univariate-z, and GLS methods.
  • Performance was evaluated for testing homogeneity of correlation matrices and estimating pooled correlation matrices.

    • Main Results:

    • Univariate-r, univariate-z, and TSSEM methods demonstrated good performance in testing homogeneity and estimating pooled correlation matrices.
    • However, only the TSSEM method performed well when fitting the SEM model itself.
    • The generalized least squares (GLS) method showed poor performance, particularly in small to medium sample sizes.

    Conclusions:

    • The proposed two-stage structural equation modeling (TSSEM) offers a robust framework for meta-analysis in SEM.
    • TSSEM outperforms traditional methods, especially in the critical step of fitting SEM models.
    • Researchers should consider TSSEM for more reliable synthesis of correlation matrices in meta-analytic SEM.