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) 2019 APA, all rights reserved).

中文翻译：

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对SEM参数具有调节作用的元分析结构方程建模。

元分析结构方程建模（MASEM）是一种越来越流行的元分析技术，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），说明效应量之间的抽样协方差，并提供假设模型在荟萃分析数据上的总体拟合度的度量。我们提出了一种新颖的MASEM方法，即一级MASEM，它比现有方法更适合于解释研究水平的异质性。一级MASEM允许研究人员将连续或类别的主持人并入MASEM，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）都可以由主持人变量建模，而该方法不需要荟萃分析中所包含的主要研究的完整数据。我们在两个真实的数据集上说明了该新方法，并通过计算机仿真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，以协助研究人员应用一级MASEM。我们通过提出一些未来的研究方向来结束本文。（PsycINFO数据库记录（c）2019 APA，保留所有权利）。