Testing Mediation and Suppression Effects of Latent Variables: Bootstrapping With Structural Equation Models
Abstract
Because of the importance of mediation studies, researchers have been continuously searching for the best statistical test for mediation effect. The approaches that have been most commonly employed include those that use zero-order and partial correlation, hierarchical regression models, and structural equation modeling (SEM). This study extends MacKinnon and colleagues (MacKinnon, Lockwood, Hoffmann, West, & Sheets, 2002; MacKinnon, Lockwood, & Williams, 2004, MacKinnon, Warsi, & Dwyer, 1995) works by conducting a simulation that examines the distribution of mediation and suppression effects of latent variables with SEM, and the properties of confidence intervals developed from eight different methods. Results show that SEM provides unbiased estimates of mediation and suppression effects, and that the bias-corrected bootstrap confidence intervals perform best in testing for mediation and suppression effects. Steps to implement the recommended procedures with Amos are presented.
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The bootstrapped confidence intervals for the model did not materially alter any of the conclusions: all regression weights reported retained their significance, with the exception of the link between conservatism and acceptance of vaccinations, which failed to reach conventional significance levels.
“The bootstrapped confidence intervals for the model in Figure 2 did not materially alter any of the conclusions: All regression weights reported in the figure retained their significance, with the exception of the link between conservatism and acceptance of vaccinations, which failed to reach conventional significance levels ().”
From The Role of Conspiracist Ideation and Worldviews in Predicting Rejection of Science (2013) · cites this paper as [36]
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“We used path analysis to assess multiple mediators and dependent variables simultaneously (Cheung and Lau, 2008).”
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Method
- Authors
- Cheung, G. W., & Lau, R. S.
- Affiliations
- Chinese University of Hong Kong (HK)
- Virginia Tech (US)
- Venue
- Organizational Research Methods
- Publisher
- SAGE Publications
- Published
- 2007-07-23
- Volume
- 11
- Issue
- 2
- Pages
- 296-325
- ISSN
- 1094-4281 (ISSN-L)
- 1552-7425
- OpenAlex
- W2132605910
- Cited by
- 1,965
- References
- 46
- Citations by year
- 2026: 107 · 2025: 135 · 2024: 134 · 2023: 184 · 2022: 164 · 2021: 175 · 2020: 141 · 2019: 103 · 2018: 104 · 2017: 107 · 2016: 121 · 2015: 112 · 2014: 110 · 2013: 91 · 2012: 71
- FWCI
- 19.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Organizational Research Methods (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- 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
- mediating effect, suppression effect, latent variables, structural equation modeling, bootstrap confidence intervals, bias-corrected bootstrap, simulation study, Amos
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