IDEAS home Printed from https://ideas.repec.org/p/ems/eureri/109594.html
   My bibliography  Save this paper

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
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/109594/ERS-2018-005-MKT.pdf
    Download Restriction: no
    ---><---

    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. Christophe Croux & Catherine Dehon, 2010. "Influence functions of the Spearman and Kendall correlation measures," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 497-515, November.
    3. Stephan Morgenthaler, 2007. "A survey of robust statistics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(1), pages 171-172, June.
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cerioli, Andrea & Farcomeni, Alessio, 2011. "Error rates for multivariate outlier detection," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 544-553, January.
    2. Roland Fried & Herold Dehling, 2011. "Robust nonparametric tests for the two-sample location problem," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 409-422, November.
    3. Christophe Croux & Catherine Dehon, 2010. "Influence functions of the Spearman and Kendall correlation measures," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(4), pages 497-515, November.
    4. Leonid Hanin, 2021. "Cavalier Use of Inferential Statistics Is a Major Source of False and Irreproducible Scientific Findings," Mathematics, MDPI, vol. 9(6), pages 1-13, March.
    5. Youssef Allouah & Rachid Guerraoui & L^e-Nguy^en Hoang & Oscar Villemaud, 2022. "Robust Sparse Voting," Papers 2202.08656, arXiv.org, revised Jan 2024.
    6. Eugster, Manuel J.A. & Leisch, Friedrich, 2011. "Weighted and robust archetypal analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1215-1225, March.
    7. repec:jss:jstsof:32:i03 is not listed on IDEAS
    8. Todorov, Valentin & Filzmoser, Peter, 2009. "An Object-Oriented Framework for Robust Multivariate Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 32(i03).
    9. Andreas Alfons & Wolfgang Baaske & Peter Filzmoser & Wolfgang Mader & Roland Wieser, 2011. "Robust variable selection with application to quality of life research," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(1), pages 65-82, March.
    10. George Djolov, 2014. "Business concentration through the eyes of the HHI," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 7(2), pages 105-127, September.
    11. Omar Al-Ubaydli & John List & Claire Mackevicius & Min Sok Lee & Dana Suskind, 2019. "How Can Experiments Play a Greater Role in Public Policy? 12 Proposals from an Economic Model of Scaling," Artefactual Field Experiments 00679, The Field Experiments Website.
    12. Pablo Aragonés‐Beltrán & Mª. Carmen González‐Cruz & Astrid León‐Camargo & Rosario Viñoles‐Cebolla, 2023. "Assessment of regional development needs according to criteria based on the Sustainable Development Goals in the Meta Region (Colombia)," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(2), pages 1101-1121, April.
    13. La Vecchia, Davide & Camponovo, Lorenzo & Ferrari, Davide, 2015. "Robust heart rate variability analysis by generalized entropy minimization," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 137-151.
    14. Hensel, Przemysław G., 2019. "Supporting replication research in management journals: Qualitative analysis of editorials published between 1970 and 2015," European Management Journal, Elsevier, vol. 37(1), pages 45-57.
    15. Valéry Dongmo Jiongo & Pierre Nguimkeu, 2018. "Bootstrapping Mean Squared Errors of Robust Small-Area Estimators: Application to the Method-of-Payments Data," Staff Working Papers 18-28, Bank of Canada.
    16. Michael Lounsbury & Christine M. Beckman, 2015. "Celebrating Organization Theory," Journal of Management Studies, Wiley Blackwell, vol. 52(2), pages 288-308, March.
    17. La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2023. "A higher-order correct fast moving-average bootstrap for dependent data," Journal of Econometrics, Elsevier, vol. 235(1), pages 65-81.
    18. Liang Wu & Lin Guan & Feng Li & Qi Zhao & Yingjun Zhuo & Peng Chen & Yaotang Lv, 2018. "Optimal Dynamic Reactive Power Reserve for Wind Farms Addressing Short-Term Voltage Issues Caused by Wind Turbines Tripping," Energies, MDPI, vol. 11(7), pages 1-15, July.
    19. Umut Asan & Ayberk Soyer, 2022. "A Weighted Bonferroni-OWA Operator Based Cumulative Belief Degree Approach to Personnel Selection Based on Automated Video Interview Assessment Data," Mathematics, MDPI, vol. 10(9), pages 1-33, May.
    20. Ebersberger, Bernd & Galia, Fabrice & Laursen, Keld & Salter, Ammon, 2021. "Inbound Open Innovation and Innovation Performance: A Robustness Study," Research Policy, Elsevier, vol. 50(7).
    21. Michael Pfarrhofer, 2020. "Forecasts with Bayesian vector autoregressions under real time conditions," Papers 2004.04984, arXiv.org.

    More about this item

    Keywords

    Mediation analysis; robust statistics; linear regression; bootstrap;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ems:eureri:109594. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/erimanl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.