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Controlling for spurious moderation in marketing: A review of statistical techniques

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  • Daryanto, Ahmad
  • Lukas, Bryan A.

Abstract

Studies in marketing rarely control for spurious moderation, which occurs when unmeasured nonlinear terms affect researchers’ moderation analyses. Spurious moderation can lead to false-positive research conclusions. With a focus on testing moderation hypotheses with multiple regression analysis and covariance-based structural equation modelling, we discuss techniques and, where relevant, develop programming code for modifying these methods so that spurious moderation can be controlled for. After demonstrating the control techniques’ effectiveness with simulated data, we set out guidelines for their use, with particular attention paid to confirmatory research traditions in marketing research.

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  • 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.
    • Handle: RePEc:eee:jbrese:v:144:y:2022:i:c:p:180-192
    DOI: 10.1016/j.jbusres.2021.12.049
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    Cited by:

    1. 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.

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