Abstract
Abstract 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. Copyright © 2010 John Wiley & Sons, Ltd.
Keywords
ModerationMeta-analysisPsychologyNarrativeAudience measurementInteractionMeta-regressionValue (mathematics)Management scienceSocial psychologyComputer sciencePolitical scienceEconomics
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Publication Info
- Year
- 2010
- Type
- article
- Volume
- 32
- Issue
- 8
- Pages
- 1033-1043
- Citations
- 186
- Access
- Closed
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Cite This
Herman Aguinis,
Ryan K. Gottfredson,
Thomas A. Wright
(2010).
Best‐practice recommendations for estimating interaction effects using meta‐analysis.
Journal of Organizational Behavior
, 32
(8)
, 1033-1043.
https://doi.org/10.1002/job.719
Identifiers
- DOI
- 10.1002/job.719