结构方程建模
范畴变量
适度
计算机科学
协方差
路径分析(统计学)
路径(计算)
统计
潜变量
数据挖掘
计量经济学
数学
人工智能
机器学习
程序设计语言
作者
Suzanne Jak,Mike W.‐L. Cheung
出处
期刊:Psychological Methods
[American Psychological Association]
日期:2019-10-31
卷期号:25 (4): 430-455
被引量:150
摘要
Meta-analytic structural equation modeling (MASEM) is an increasingly popular metaanalytic technique that combines the strengths of meta-analysis and structural equation modeling.MASEM facilitates the evaluation of complete theoretical models (e.g., path models or factor analytic models), accounts for sampling covariance between effect sizes, and provides measures of overall fit of the hypothesized model on meta-analytic data.We propose a novel MASEM method, One-Stage MASEM, which is better suitable to explain study-level heterogeneity than existing methods.One-Stage MASEM allows researchers to incorporate continuous or categorical moderators into the MASEM, in which any parameter in the structural equation model (e.g., path coefficients and factor loadings) can be modeled by the moderator variable, while the method does not require complete data for the primary studies included in the meta-analysis.We illustrate the new method on two real datasets, evaluate its empirical performance via a computer simulation study, and provide user-friendly R-functions and annotated syntax to assist researchers in applying One-Stage MASEM.We close the paper by presenting several future research directions.
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