plssem : A Stata Package for Structural Equation Modeling with Partial Least Squares

We provide a package called plssem that fits partial least squares structural equation models, which is often considered an alternative to the commonly known covariance-based structural equation modeling. plssem is developed in line with the algorithm provided by Wold (1975) and Lohmöller (1989). To...

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Bibliographic Details
Published in:Journal of statistical software 2019-03, Vol.88 (8), p.1-35
Main Authors: Venturini, Sergio, Mehmetoglu, Mehmet
Format: Article
Language:English
Subjects:
factor analysis
latent variables
partial least squares
path models
pls
pls-pm
pls-sem
sem
stata
structural equation modeling
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Summary:We provide a package called plssem that fits partial least squares structural equation models, which is often considered an alternative to the commonly known covariance-based structural equation modeling. plssem is developed in line with the algorithm provided by Wold (1975) and Lohmöller (1989). To demonstrate its features, we present an empirical application on the relationship between perception of self-attractiveness and two specific types of motivations for working out using a real-life data set. In the paper we also show that, in line with other software performing structural equation modeling, plssem can be used for putting in relation single-item observed variables too and not only for latent variable modeling.
ISSN:1548-7660
1548-7660
DOI:10.18637/jss.v088.i08