Organizational Research Methods

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Register here to gain access to SAGE's 500+ Journals Online

Click here to sign up for SAGE Journal Email Alerts today!

Sign In to gain access to subscriptions and/or personal tools.
This Article
Right arrow Full Text (PDF)
Right arrow All Versions of this Article:
1094428107300343v1
11/2/296    most recent
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (2)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Cheung, G. W.
Right arrow Articles by Lau, R. S.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?
This version was published on April 1, 2008
Organizational Research Methods, Vol. 11, No. 2, 296-325 (2008)
DOI: 10.1177/1094428107300343

Testing Mediation and Suppression Effects of Latent Variables

Bootstrapping With Structural Equation Models

Gordon W. Cheung

The Chinese University of Hong Kong

Rebecca S. Lau

Virginia Polytechnic Institute and State University

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.

Key Words: mediating effects • suppression effects • structural equation modeling


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
 Organizational Research MethodsHome page
D. A. Kenny
Reflections on Mediation
Organizational Research Methods, April 1, 2008; 11(2): 353 - 358.
[Abstract] [PDF]

Home page
 Organizational Research MethodsHome page
J. E. Mathieu, R. P. DeShon, and D. D. Bergh
Mediational Inferences in Organizational Research: Then, Now, and Beyond
Organizational Research Methods, April 1, 2008; 11(2): 203 - 223.
[Abstract] [PDF]