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Structural equation modeling with partial least squares using Stata

Author

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  • Sergio Venturini

    (Univeristà Cattolica del Sacro Cuore, Cremona)

  • Mehmet Mehmetoglu

    (Norwegian University of Science and Technology)

Abstract

Structural equation modeling (SEM) is a multivariate statistical framework that can model both observed and unobserved (latent) variables through complex relationships. In this talk, we present plssem, a community-contributed Stata package for partial least-squares SEM, an approach to SEM which has attracted a lot of interest in the last 20 years from an increasing number of researchers and practitioners from many Felds such as marketing, information systems, economics, psychology, and others. After introducing the topic to the audience, we will illustrate the current architecture of the package and its main features.

Suggested Citation

  • Sergio Venturini & Mehmet Mehmetoglu, 2024. "Structural equation modeling with partial least squares using Stata," Italian Stata Users' Group Meetings 2024 01, Stata Users Group.
    • Handle: RePEc:boc:isug24:01
    as

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    File URL: http://repec.org/isug2024/Italy24_Venturini.pdf
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    References listed on IDEAS

    as
    1. Monecke, Armin & Leisch, Friedrich, 2012. "semPLS: Structural Equation Modeling Using Partial Least Squares," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i03).
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