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You Write, but Others Read: Common Methodological Misunderstandings in PLS and Related Methods

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New Perspectives in Partial Least Squares and Related Methods

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 56))

Abstract

PLS and related methods are currently enjoying widespread popularity in part due to the availability of easy to use computer programs that require very little technical knowledge. Most of these methods focus on examining a fit function with respect to a set of free or constrained parameters for a given collection of data under certain assumptions. Although much has been written about the assumptions underpinning these methods, many misconceptions are prevalent among users and sometimes even appear in premier scholarly journals. In this chapter, we discuss a variety of methodological misunderstandings that warrant careful consideration before indiscriminately applying these methods.

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Notes

  1. 1.

    These generation of Monte Carlo data can easily be done using the statistical analysis program Mplus [8]. M plus has a fairly easy-to-use interface and offers researchers a flexible tool to analyze data using all kinds of model choices. Detailed illustrations for using the m plus Monte Carlo simulation options can also be found in [93], in the m plus User’s Guide [8], and at the product Web site www.statmodel.com

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Authors and Affiliations

  1. Research Methods and Statistics, Graduate School of Education and Interdepartmental Graduate Program in Management, A. Gary Anderson Graduate School of Management, University of California, Riverside, CA, 925121, USA

    George A. Marcoulides

  2. Department of Decision and Information Systems, C. T. Bauer College of Business, University of Houston, Houston, TX, 77204-6021, USA

    Wynne W. Chin

Authors
  1. George A. Marcoulides
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  2. Wynne W. Chin
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Correspondence to George A. Marcoulides .

Editor information

Editors and Affiliations

  1. School of Behavioral & Brain Sciences, The University of Texas at Dallas, Richardson, Texas, USA

    Herve Abdi

  2. Department of Decision and Information Systems, University of Houston, Houston, Texas, USA

    Wynne W. Chin

  3. ESSEC Business School of Paris, Cergy-Pontoise Cedex, France

    Vincenzo Esposito Vinzi

  4. CNAM, Paris, USA

    Giorgio Russolillo

  5. Rouen Business School, Rouen, France

    Laura Trinchera

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Marcoulides, G.A., Chin, W.W. (2013). You Write, but Others Read: Common Methodological Misunderstandings in PLS and Related Methods. In: Abdi, H., Chin, W., Esposito Vinzi, V., Russolillo, G., Trinchera, L. (eds) New Perspectives in Partial Least Squares and Related Methods. Springer Proceedings in Mathematics & Statistics, vol 56. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8283-3_2

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