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A Generalized Solution for Approximating the Power to Detect Effects of Categorical Moderator Variables Using Multiple Regression

University of Colorado at Denver

Robert J. Boik

Charles A. Pierce

Montana State University

Investigators in numerous organization studies disciplines are concerned about the low statistical power of moderated multiple regression (MMR) to detect effects of categorical moderator variables. The authors provide a theoretical approximation to the power of MMR. The theoretical result confirms, synthesizes, and extends previous Monte Carlo research on factors that affect the power of MMR tests of categorical moderator variables and the low power of MMR in typical research situations. The authors develop and describe a computer program, which is available on the Internet, that allows researchers to approximate the power of MMR to detect the effects of categorical moderator variables given user-input information (e.g., sample size, reliability of measurement). The approximation also allows investigators to determine the effects of violating certain assumptions required for MMR. Given the typically low power of MMR, researchers are encouraged to use the computer program to approximate power while planning their research design and methodology.

Organizational Research Methods, Vol. 4, No. 4, 291-323 (2001)
DOI: 10.1177/109442810144001


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