Signal-to-noise ratio in estimating and testing the mediation effect: structural equation modeling versus path analysis with weighted composites
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Publication:6657617
DOI10.1007/s11336-024-09975-4MaRDI QIDQ6657617
Zhi Yong Zhang, Lijuan Wang, Ke-Hai Yuan
Publication date: 6 January 2025
Published in: Psychometrika (Search for Journal in Brave)
signal-to-noise ratiostructural equation modelingindirect effectmeasurement reliabilityfactor-score regression
Cites Work
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- A unified approach to exploratory factor analysis with missing data, nonnormal data, and in the presence of outliers
- On robustness of the normal-theory based asymptotic distributions of three reliability coefficient estimates
- The asymptotic effect of substituting estimators for parameters in certain types of statistics
- Estimating equations with nuisance parameters: Theory and applications
- Regression among factor scores
- A note on residual M‐distances for identifying aberrant response patterns
- Some Effects of Errors of Measurement on Multiple Correlation
- Which method delivers greater signal‐to‐noise ratio: Structural equation modelling or regression analysis with weighted composites?
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