Best-practice recommendations for estimating interaction effects using meta-analysis

One of the key advantages of meta-analysis (i.e., a quantitative literature review) over a narrative literature review is that it allows for formal tests of interaction effects—namely, whether the relationship between two variables is contingent upon the value of another (moderator) variable. Intera...

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Bibliographic Details
Published in:Journal of organizational behavior 2011-11, Vol.32 (8), p.1033-1043
Main Authors: Aguinis, Herman, Gottfredson, Ryan K., Wright, Thomas A.
Format: Article
Language:English
Subjects:
Accuracy
Best practice
Confidence interval
Data collection
Estimating techniques
Estimation methods
literature review
Literature reviews
Meta analysis
methodology
Modeling
Moderator variables
Narratives
Organization theory
Organizational behavior
Readership
Recommendations
Research design
Research methods
research synthesis
Researcher's Notebook
Statistical variance
Studies
Systematic review
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Summary:One of the key advantages of meta-analysis (i.e., a quantitative literature review) over a narrative literature review is that it allows for formal tests of interaction effects—namely, whether the relationship between two variables is contingent upon the value of another (moderator) variable. Interaction effects play a central role in organizational science research because they highlight boundary conditions of a theory: Conditions under which relationships change in strength and/or direction. This article describes procedures for estimating interaction effects using meta-analysis, distills the technical literature for a general readership of organizational science researchers, and includes specific best-practice recommendations regarding actions researchers can take before and after data collection to improve the accuracy of substantive conclusions regarding interaction effects investigated meta-analytically.
ISSN:0894-3796
1099-1379
DOI:10.1002/job.719