Skip to main navigation Skip to search Skip to main content

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

  • Norwegian University of Science and Technology

Research output: Contribution to journalArticlepeer-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.
Original languageEnglish
Pages (from-to)1-35
Number of pages35
JournalJournal of Statistical Software
Issue number88/8
DOIs
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Software
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

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

Fingerprint

Dive into the research topics of 'plssem: A Stata Package for Structural Equation Modeling with Partial Least Squares'. Together they form a unique fingerprint.

Cite this