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

被引:213
|
作者
Aguinis, Herman [1 ]
Gottfredson, Ryan K. [1 ]
机构
[1] Indiana Univ, Kelley Sch Business, Dept Management & Entrepreneurship, Bloomington, IN 47405 USA
关键词
ERROR VARIANCE; CORRELATION-COEFFICIENTS; CATEGORICAL VARIABLES; POWER; HETEROGENEITY; COARSE; SIZE;
D O I
10.1002/job.686
中图分类号
F [经济];
学科分类号
02 ;
摘要
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 (C) 2010 John Wiley & Sons, Ltd.
引用
收藏
页码:776 / 786
页数:11
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