University of Amsterdam.
Department of Psychology.
Psychol Methods. 2020 Aug;25(4):430-455. doi: 10.1037/met0000245. Epub 2019 Oct 31.
Meta-analytic structural equation modeling (MASEM) is an increasingly popular meta-analytic 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 data sets, 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 article by presenting several future research directions. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
元分析结构方程建模（MASEM）是一种越来越流行的元分析技术，它结合了元分析和结构方程建模的优势。MASEM 有助于评估完整的理论模型（例如，路径模型或因子分析模型），解释效应量之间的样本协方差，并提供对元分析数据中假设模型的整体拟合度的度量。我们提出了一种新颖的 MASEM 方法，即单阶段 MASEM，与现有方法相比，它更适合解释研究水平的异质性。单阶段 MASEM 允许研究人员将连续或分类的调节变量纳入 MASEM 中，其中结构方程模型中的任何参数（例如，路径系数和因子载荷）都可以由调节变量建模，而该方法不需要元分析中包含的主要研究的完整数据。我们在两个真实数据集上演示了新方法，通过计算机模拟研究评估了其经验性能，并提供了用户友好的 R 函数和带注释的语法，以帮助研究人员应用单阶段 MASEM。最后，我们提出了几个未来的研究方向。（PsycInfo 数据库记录（c）2020 APA，保留所有权利）。
