Home > Research > Publications & Outputs > Controlling for spurious moderation in marketing

Research

Electronic data

  • index_spurious

    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Business Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Business Research, 144, 2022 DOI: 10.1016/j.busres.2021.12.049

    Accepted author manuscript, 980 KB, PDF document

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

Links

Text available via DOI:

Keywords

View graph of relations

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

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Controlling for spurious moderation in marketing: A review of statistical techniques. / Daryanto, Ahmad; Lukas, Bryan.
In: Journal of Business Research, Vol. 144, 31.05.2022, p. 180-192.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Daryanto, A & Lukas, B 2022, 'Controlling for spurious moderation in marketing: A review of statistical techniques', Journal of Business Research, vol. 144, pp. 180-192. https://doi.org/10.1016/j.jbusres.2021.12.049

APA

Daryanto, A., & Lukas, B. (2022). Controlling for spurious moderation in marketing: A review of statistical techniques. Journal of Business Research, 144, 180-192. https://doi.org/10.1016/j.jbusres.2021.12.049

Vancouver

Daryanto A, Lukas B. Controlling for spurious moderation in marketing: A review of statistical techniques. Journal of Business Research. 2022 May 31;144:180-192. Epub 2022 Feb 8. doi: 10.1016/j.jbusres.2021.12.049

Author

Daryanto, Ahmad ; Lukas, Bryan. / Controlling for spurious moderation in marketing : A review of statistical techniques. In: Journal of Business Research. 2022 ; Vol. 144. pp. 180-192.

Bibtex

@article{2d01cd3142694d6ba2518b3f666fc2cb,
title = "Controlling for spurious moderation in marketing: A review of statistical techniques",
abstract = "Studies in marketing rarely control for spurious moderation, which occurs when unmeasured nonlinear terms affect researchers{\textquoteright} 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{\textquoteright} effectiveness with simulated data, we set out guidelines for their use, with particular attention paid to confirmatory research traditions in marketing research.",
keywords = "Spurious moderation, Interaction effects, Unmeasured nonlinear effects, Multiple regression analysis, Covariance-based structural equation modelling",
author = "Ahmad Daryanto and Bryan Lukas",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Journal of Business Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Business Research, 144, 2022 DOI: 10.1016/j.busres.2021.12.049",
year = "2022",
month = may,
day = "31",
doi = "10.1016/j.jbusres.2021.12.049",
language = "English",
volume = "144",
pages = "180--192",
journal = "Journal of Business Research",
issn = "0148-2963",
publisher = "Elsevier Inc.",

}

RIS

TY - JOUR

T1 - Controlling for spurious moderation in marketing

T2 - A review of statistical techniques

AU - Daryanto, Ahmad

AU - Lukas, Bryan

N1 - This is the author’s version of a work that was accepted for publication in Journal of Business Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Business Research, 144, 2022 DOI: 10.1016/j.busres.2021.12.049

PY - 2022/5/31

Y1 - 2022/5/31

N2 - 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.

AB - 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.

KW - Spurious moderation

KW - Interaction effects

KW - Unmeasured nonlinear effects

KW - Multiple regression analysis

KW - Covariance-based structural equation modelling

U2 - 10.1016/j.jbusres.2021.12.049

DO - 10.1016/j.jbusres.2021.12.049

M3 - Journal article

VL - 144

SP - 180

EP - 192

JO - Journal of Business Research

JF - Journal of Business Research

SN - 0148-2963

ER -