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Testing Mediation and Suppression Effects of Latent Variables: Bootstrapping With Structural Equation Models

Organizational research methods, 2008-04, Vol.11 (2), p.296-325 [Peer Reviewed Journal]

Copyright SAGE PUBLICATIONS, INC. Apr 2008 ;ISSN: 1094-4281 ;EISSN: 1552-7425 ;DOI: 10.1177/1094428107300343

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  • Title:
    Testing Mediation and Suppression Effects of Latent Variables: Bootstrapping With Structural Equation Models
  • Author: Cheung, Gordon W. ; Lau, Rebecca S.
  • Subjects: Bootstrap method ; Computer simulation ; Confidence intervals ; Impact analysis ; Mathematical analysis ; Mathematical models ; Mediation ; Regression ; Scanning electron microscopy ; Simulation ; Statistical tests ; Studies
  • Is Part Of: Organizational research methods, 2008-04, Vol.11 (2), p.296-325
  • Description: 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.
  • Publisher: London, England: Sage Publications
  • Language: English
  • Identifier: ISSN: 1094-4281
    EISSN: 1552-7425
    DOI: 10.1177/1094428107300343
  • Source: Alma/SFX Local Collection
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