结构方程建模
计算机科学
应用数学
数学
机器学习
作者
Amin Raeisi‐Vanani,Luke Plonsky,Wei Wang,Kejin Lee,Peng Peng
出处
期刊:Research methods in applied linguistics
[Elsevier]
日期:2022-12-01
卷期号:1 (3): 100018-100018
被引量:3
标识
DOI:10.1016/j.rmal.2022.100018
摘要
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.
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