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Best-practice recommendations for estimating interaction effects using moderated multiple regression

✍ Scribed by Herman Aguinis; Ryan K. Gottfredson

Book ID
102391960
Publisher
John Wiley and Sons
Year
2010
Tongue
English
Weight
100 KB
Volume
31
Category
Article
ISSN
0894-3796

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✦ Synopsis

Abstract

An interaction effect indicates that a relationship is contingent upon the values of another (moderator) variable. Thus, interaction effects describe conditions under which relationships change in strength and/or direction. Understanding interaction effects is essential for the advancement of the organizational sciences because they highlight a theory's boundary conditions. We describe procedures for estimating and interpreting interaction effects using moderated multiple regression (MMR). We distill the technical literature for a general readership of organizational science researchers and include specific best‐practice recommendations regarding actions researchers can take before and after data collection to improve the accuracy of MMR‐based conclusions regarding interaction effects. Copyright © 2010 John Wiley & Sons, Ltd.

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## 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) var