Applying meta-analytic structural equation modeling to second language research: An introduction

Amin Raeisi-Vanani, Luke Plonsky, Wei Wang, Kejin Lee, Peng Peng

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Structural equation modeling (SEM) and meta-analysis (MA) are both powerful techniques employed frequently throughout the social and behavioral sciences, including applied linguistics. Although meta-analytic data are typically analyzed by calculating weighted means or correlation coefficients, other statistical models such as SEM can also be applied (Schoemann, 2016). SEM models gauge conceptualized models vis-à-vis empirical data across a given domain. Despite a considerable expansion of the analytical repertoire in applied linguistics in recent years (Gass, Loewen, & Plonsky, 2021), this particular technique has yet to be formally introduced or applied. The present methods tutorial, therefore, aims to introduce MASEM to applied linguistics. In doing so, we provide a conceptual rationale for MASEM, an outline of major stages involved, and a worked example of how MASEM might be utilized in the field, along with the data and code necessary for re-running all analyses.

Original languageEnglish (US)
Article number100018
JournalResearch Methods in Applied Linguistics
Volume1
Issue number3
DOIs
StatePublished - Dec 2022

Keywords

  • L2 research
  • MASEM
  • Meta-analysis
  • Quantitative research methods
  • Structural equation modeling (SEM)

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Linguistics and Language

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