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

Sergio Venturini, Mehmet Mehmetoglu

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

Abstract

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.
Lingua originaleEnglish
pagine (da-a)1-35
Numero di pagine35
RivistaJournal of Statistical Software
DOI
Stato di pubblicazionePubblicato - 2019

Keywords

  • PLS
  • PLS-PM
  • PLS-SEM
  • SEM
  • Stata
  • factor analysis
  • latent variables
  • partial least squares
  • path models
  • structural equation modeling

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