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Probing three-way interactions in moderated multiple regression: Development and application of a slope difference test.

Journal of Applied Psychology · 2006 · Vol. 91(4) · pp. 917–926
Jeremy DawsonAndreas W. Richter

Abstract

Researchers often use 3-way interactions in moderated multiple regression analysis to test the joint effect of 3 independent variables on a dependent variable. However, further probing of significant interaction terms varies considerably and is sometimes error prone. The authors developed a significance test for slope differences in 3-way interactions and illustrate its importance for testing psychological hypotheses. Monte Carlo simulations revealed that sample size, magnitude of the slope difference, and data reliability affected test power. Application of the test to published data yielded detection of some slope differences that were undetected by alternative probing techniques and led to changes of results and conclusions. The authors conclude by discussing the test's applicability for psychological research.

Psychometric Methodologies and TestingSensory Analysis and Statistical MethodsAdvanced Statistical Methods and ModelsPsychologyStatisticsTest (biology)Monte Carlo methodReliability (semiconductor)Regression analysisSample size determinationStatistical hypothesis testingVariablesRegression

MeSH terms

EmploymentHumansModels, PsychologicalRegression Analysis
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Probing three-way interactions in moderated multiple regression: Development and application of a slope difference test. · Scinovex