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Have your cake and eat it too: PLSe2 = ML + PLS

Author

Listed:
  • Majid Ghasemy

    (Universiti Sains Malaysia (USM))

  • Hazri Jamil

    (Universiti Sains Malaysia (USM))

  • James E. Gaskin

    (Brigham Young University)

Abstract

PLSe1 and PLSe2 methods were developed in 2013. While the performance of PLSe1 under normality and non-normality conditions has been confirmed, the performance of PLSe2, proposed to provide an avenue for the resurrection of PLS as a fully justified statistical methodology, has not yet been verified under non-normality condition. For this reason, our study aims at testing the performance of PLSe2 with non-normal data based on a Monte Carlo simulation using a simple and a complex model. In addition, it aims at providing a step-by-step visual guideline on how to apply this method in estimating a simple mediation model using EQS 6.4. The results of the Monte Carlo simulations across different numbers of replications and sample sizes provided substantial support for the performance of PLSe2 under non-normality conditions since the produced estimates were unbiased and virtually identical to the parameters resulted from the traditional ML estimation. In addition, we provided evidence about the suitability of different robust test statistics for the purpose of model evaluation based on our simulation results. Regarding the empirical example, we estimated a mediation model using ML, PLSe2, and PLSc estimators, compared the results across these methods, and provided further support for our PLSe2 and ML results through running a resampling bootstrap simulation. Overall, while we empirically validated the PLSe2 method using Monte Carlo simulations, our findings suggest that PLSe2 has the advantages of both ML and PLS and performs well under non-normality (and normality) conditions, thereby suggesting it as the methodology of choice for model specification, estimation, and evaluation in social sciences empirical studies.

Suggested Citation

  • Majid Ghasemy & Hazri Jamil & James E. Gaskin, 2021. "Have your cake and eat it too: PLSe2 = ML + PLS," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 497-541, April.
    • Handle: RePEc:spr:qualqt:v:55:y:2021:i:2:d:10.1007_s11135-020-01013-6
    DOI: 10.1007/s11135-020-01013-6
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    References listed on IDEAS

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    Cited by:

    1. Majid Ghasemy & Farhah Muhammad & Jamshid Jamali & José Luis Roldán, 2021. "Satisfaction and Performance of the International Faculty: To What Extent Emotional Reactions and Conflict Matter?," SAGE Open, , vol. 11(3), pages 21582440211, July.
    2. Majid Ghasemy & Leila Mohajer & Lena Frömbling & Mehrdad Karimi, 2021. "Faculty Members in Polytechnics to Serve the Community and Industry: Conceptual Skills and Creating Value for the Community—The Two Main Drivers," SAGE Open, , vol. 11(3), pages 21582440211, September.
    3. El Baz, Jamal & Ruel, Salomée & Jebli, Fedwa, 2023. "Harnessing supply chain resilience and social performance through safety and health practices in the COVID-19 era: An investigation of normative pressures and adoption timing's role," International Journal of Production Economics, Elsevier, vol. 264(C).
    4. Majid Ghasemy & Isabel Maria Rosa-Díaz & James Eric Gaskin, 2021. "The Roles of Supervisory Support and Involvement in Influencing Scientists’ Job Satisfaction to Ensure the Achievement of SDGs in Academic Organizations," SAGE Open, , vol. 11(3), pages 21582440211, July.

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