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

Jeremy Dawson, Andreas W. Richter

Journal of Applied Psychology · 2006 · 1.8K citations · 35 references

Concepts

TL;DR

Researchers frequently use 3‑way interactions in moderated multiple regression to assess joint effects of three predictors, but probing significant terms is inconsistent and error‑prone. The authors developed a significance test for slope differences in 3‑way interactions to evaluate psychological hypotheses. They created a slope‑difference test for 3‑way interactions, demonstrating its use in probing psychological hypotheses. Simulations showed that power depends on sample size, slope‑difference magnitude, and data reliability, and applying the test to published data uncovered slope differences missed by other methods, altering results and conclusions and underscoring its usefulness in psychological research.

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.

References

35