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

被引：224

作者：

Aguinis, Herman ^{[1
]}

Gottfredson, Ryan K. ^{[1
]}

机构：

[1] Indiana Univ, Kelley Sch Business, Dept Management & Entrepreneurship, Bloomington, IN 47405 USA

来源：

JOURNAL OF ORGANIZATIONAL BEHAVIOR | 2010年 / 31卷 / 06期

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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