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Assessing moderator effects, main effects, and simple effects without collinearity problems in moderated regression models

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  • Park, Sang-June
  • Yi, Youjae

Abstract

It is common to assess moderation effects with moderated regression analysis. If the interaction effect is detected by moderated regression analysis, one may subsequently assess the simple effect of the focal predictor with simple slopes analysis. However, the two traditional analyses may suffer from considerable correlations among predictors. These correlations lead to correlations among the individual effects of predictors and thus may make it difficult to detect the interaction effect, the simple effect, and the main effects of the focal predictor and the moderator with the two traditional analyses. This paper suggests alternative analyses assessing the various effects without the collinearity problem. The alternative analyses provide the statistics for the various effects derived from the confidence-interval estimate for the overall effect size of predictors. In addition, this paper presents a practical guideline for assessing the various effects with the traditional analyses as well as the alternative analyses.

Suggested Citation

  • Park, Sang-June & Yi, Youjae, 2022. "Assessing moderator effects, main effects, and simple effects without collinearity problems in moderated regression models," Journal of Business Research, Elsevier, vol. 145(C), pages 905-919.
    • Handle: RePEc:eee:jbrese:v:145:y:2022:i:c:p:905-919
    DOI: 10.1016/j.jbusres.2022.03.018
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    References listed on IDEAS

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    1. Raj Echambadi & James D. Hess, 2007. "Mean-Centering Does Not Alleviate Collinearity Problems in Moderated Multiple Regression Models," Marketing Science, INFORMS, vol. 26(3), pages 438-445, 05-06.
    2. Daryanto, Ahmad & Lukas, Bryan A., 2022. "Controlling for spurious moderation in marketing: A review of statistical techniques," Journal of Business Research, Elsevier, vol. 144(C), pages 180-192.
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    Cited by:

    1. Park, Sang-June & Yi, Youjae, 2023. "Decomposing main effects in moderated regression models," Journal of Business Research, Elsevier, vol. 157(C).
    2. Aditya Aji Prabhawa & Iman Harymawan, 2022. "Readability of Financial Footnotes, Audit Fees, and Risk Management Committee," Risks, MDPI, vol. 10(9), pages 1-21, August.

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