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More powerful parameter tests? No, rather biased parameter estimates. Some reflections on path analysis with weighted

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Behavior Research Methods
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Summary

This study challenges previous findings, arguing that covariance-based structural equation modeling (CB-SEM) can achieve comparable or greater effect sizes and statistical power than path analysis with weighted composites. Re-analysis suggests CB-SEM

Keywords:
Covariance-based structural equation modelingEffect sizeMeasurement errorPLS-SEMPartial least squares path modeling

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Area of Science:

  • Quantitative Psychology
  • Statistical Modeling
  • Behavior Research Methods

Background:

  • A recent study (Deng & Yuan, 2023) concluded path analysis with weighted composites outperforms covariance-based structural equation modeling (CB-SEM) in effect size and statistical power.
  • This conclusion was based on a meta-comparison of nine empirical datasets and eleven models.

Purpose of the Study:

  • To object to the central conclusion of Deng & Yuan (2023).
  • To demonstrate limitations in the justification and study design of the original comparison.
  • To re-evaluate the performance of CB-SEM versus path analysis using different scaling methods.

Main Methods:

  • Critique of the theoretical justification for comparing CB-SEM and path analysis via weighted composites.
  • Analysis of the limitations inherent in meta-comparison study designs.
  • Replication of Deng and Yuan's meta-comparison with an alternative scaling method for CB-SEM.

Main Results:

  • The justification for comparing CB-SEM and path analysis via weighted composites is not well-grounded.
  • Meta-comparison designs have significant limitations for comparing statistical methods.
  • CB-SEM using normal-distribution-based maximum likelihood estimation does not necessarily yield smaller effect sizes than path analysis with composites when an alternative scaling method is used.

Conclusions:

  • The original study's conclusion regarding the superiority of path analysis via weighted composites is contested.
  • Methodological choices, including scaling, significantly impact the comparison of CB-SEM and path analysis.
  • CB-SEM remains a viable method with comparable or potentially superior performance under appropriate conditions.