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A Robust Bootstrap Test for Mediation Analysis

Author

Listed:
  • Alfons, A.
  • Ates, N.Y.
  • Groenen, P.J.F.

Abstract

Mediation analysis is central to theory building and testing in organizations research. Management scholars often use linear regression analysis based on normal-theory maximum likelihood estimators to test mediation. However, these estimators are very sensitive to deviations from normality assumptions, such as outliers or heavy tails of the observed distribution. This sensitivity seriously threatens the empirical testing of theory about mediation mechanisms, as many empirical studies lack reporting of outlier treatments and checks on model assumptions. To overcome this threat, we develop a fast and robust mediation method that yields reliable results even when the data deviate from normality assumptions. Simulation studies show that our method is both superior in estimating the effect size and more reliable in assessing its significance than the existing methods. We illustrate the mechanics of our proposed method in three empirical cases and provide freely available software in R and SPSS to enhance its accessibility and adoption by researchers and practitioners.

Suggested Citation

  • Alfons, A. & Ates, N.Y. & Groenen, P.J.F., 2018. "A Robust Bootstrap Test for Mediation Analysis," ERIM Report Series Research in Management ERS-2018-005-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    • Handle: RePEc:ems:eureri:109594
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    References listed on IDEAS

    as
    1. Stephan Morgenthaler, 2007. "A survey of robust statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 271-293, February.
    2. Stephan Morgenthaler, 2007. "A survey of robust statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(1), pages 171-172, June.
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    4. Stephan Morgenthaler, 2007. "A survey of robust statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(3), pages 271-293, February.
    5. Salibian-Barrera, Matias & Van Aelst, Stefan, 2008. "Robust model selection using fast and robust bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5121-5135, August.
    6. Richard A. Bettis, 2012. "The search for asterisks: Compromised statistical tests and flawed theories," Strategic Management Journal, Wiley Blackwell, vol. 33(1), pages 108-113, January.
    Full references (including those not matched with items on IDEAS)

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