Structural Equation Modeling with R for education scientists.

J. Jongerling, S. López-Pernas, M. Saqr, L.V.D.E. Vogelsmeier

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

3 Citations (Scopus)

Abstract

Structural Equation Modeling (SEM) is a method for modeling whole sets of complex interrelations between observed and/or latent variables. In its most common form, SEM combines confirmatory factor analysis (CFA with another method named path analysis). Just like CFA, SEM relates observed variables to latent variables that are measured by those observed variables and, as path analysis does, SEM allows for a wide range of regression-type relations between sets of variables (both latent and observed). This chapter presents an introduction to SEM, an integrated strategy for conducting SEM analysis that is well-suited for educational sciences, and a tutorial on how to carry out an SEM analysis in R.
Original languageEnglish
Title of host publicationLearning analytics methods and tutorials
Subtitle of host publicationA practical guide using R
EditorsM. Saqr, S. López-Pernas
PublisherSpringer
Pages705-721
Number of pages17
ISBN (Electronic)978-3-031-54464-4
ISBN (Print)978-3-031-54463-7
DOIs
Publication statusPublished - 2024

Keywords

  • Learning analytics
  • SEM
  • Structural equation modeling

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