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Educational and Psychological Measurement
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Statistical Power Computations for Detecting Dichotomous Moderator Variables with Moderated Multiple Regression

Herman Aguinis

University of Colorado at Denver haguinis{at}castle.cudenver.edu

Charles A. Pierce

Montana State University

A revised and improved version of Aguinis, Pierce, and Stone-Romero's (1994) program for estimating the statistical power of moderated multiple regression to detect dichotomous moderator variables is described. The Quick BASIC program runs on IBM and IBM-compatible personal computers and estimates power based on user-provided values for (a) total sample size, (b) sample sizes across the two moderator-based subgroups, (c) correlation coefficients between the predictor and criterion for each of the two moderator-based subgroups, (d) correlation coefficient between the predictor and hypothesized moderator, and (e) sample and population standard deviations for the predictor. Program-generated power estimates for typical research situations in education, psychology, and management indicate that hypothesis tests of moderating effects are typically conducted at insufficient levels of statistical power.

Educational and Psychological Measurement, Vol. 58, No. 4, 668-676 (1998)
DOI: 10.1177/0013164498058004009
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