Structural Equation Modeling in R: a practical introduction for linguists

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

This chapter provides a hands-on introduction to Structural Equation Modeling (SEM), a powerful statistical technique that can be used to test complex causal models involving multiple interconnected variables. After outlining the theoretical fundamentals of this technique, the chapter illustrates, step by step, how to perform SEM in R. The data for the analysis comes from an experimental study which investigated the psychological effects of the use of stance verbs such as know, want, believe in a persuasive genre of business discourse. In addition to offering practical guidance on how to execute SEM, the chapter aims to show that SEM lends itself well to empirical research within a cognitive linguistic framework and can help us achieve a more nuanced understanding of how language influences thought.
Original languageEnglish
Title of host publicationData Analytics in Cognitive Linguistics
Subtitle of host publicationMethods and Insights
EditorsDennis Tay, Molly Xie Pan
PublisherDe Gruyter
Pages75-102
Number of pages28
ISBN (Electronic)9783110687279
ISBN (Print)9783110687156
DOIs
Publication statusPublished - 23 May 2022

Publication series

NameApplications of Cognitive Linguistics
PublisherDe Gruyter Mouton
Volume41
ISSN (Print)1861-4078

Keywords

  • structural equation modeling
  • Cognitive Linguistics
  • Corpus Linguistics
  • R programming language

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