Abstract
There has been a long and ongoing debate, at points resembling an acrimonious dispute, among proponents and detractors of the use of the partial least squares (PLS) approach for structural equation modeling (SEM). The composite-factor estimation dichotomy has been the epicenter of this debate. In this chapter, we briefly discuss the implementation of a new method to conduct factor-based PLS-SEM analyses, which could be a solid step in the resolution of this debate. This method generates estimates of both true composites and factors, in two stages, fully accounting for measurement error. Our discussion is based on an illustrative model in the field of e-collaboration. A Monte Carlo experiment suggests that model parameters generated by the method are asymptotically unbiased. The method is implemented as part of the software WarpPLS, starting in version 5.0. This chapter provides enough details for the method’s implementation in other venues such as R and GNU Octave.
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Acknowledgments
The author is the developer of the software WarpPLS, which has over 7000 users in more than 33 different countries at the time of this writing, and moderator of the PLS-SEM e-mail distribution list. He is grateful to those users, and to the members of the PLS-SEM e-mail distribution list, for questions, comments, and discussions on topics related to SEM and to the use of WarpPLS.
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Kock, N. (2017). Going Beyond Composites: Conducting a Factor-Based PLS-SEM Analysis. In: Latan, H., Noonan, R. (eds) Partial Least Squares Path Modeling. Springer, Cham. https://doi.org/10.1007/978-3-319-64069-3_3
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DOI: https://doi.org/10.1007/978-3-319-64069-3_3
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