Journal Articles

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

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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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Detail Information

Series Title

Organizational Research Methods

Call Number

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Publisher

California : Sage Publications., 2008

Collation

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Language

English

ISBN/ISSN

1094-4281

Classification

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Content Type

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Media Type

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Carrier Type

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Edition

Vol. 11, No. 2, Page 296-325

Subject(s)

mediating effects
suppression effects
structural equation modeling

Specific Detail Info

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Statement of Responsibility

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