Reporting the reliability of the scores obtained from a scale or test is part of the standard repertoire of empirical studies in psychology. With reliability being a key concept in psychometrics, researchers have become more and more interested in evaluating reliability coefficients across studies and, ultimately, quantify and explain possible between-study variation. This approach-commonly known as "reliability generalization"-can be specified within the framework of meta-analysis. The existing procedures of reliability generalization, however, have several methodological issues: (a) unrealistic and often untested assumptions on the measurement model underlying the reliability coefficients (e.g., essential τ-equivalence for Cronbach's α); (b) the use of univariate approaches to synthesizing reliabilities of total and subscale scores; (c) the lack of comparability across different types of reliability coefficients. However, these issues can be addressed directly through meta-analytic structural equation modeling (MASEM)-a method that combines meta-analysis with structural equation modeling through synthesizing either correlation matrices or model parameters across studies. The primary objective of this article is to present the potential MASEM has for the meta-analysis of reliability coefficients. We review the extant body of literature on the use of reliability generalization, discuss and illustrate two MASEM approaches (i.e., correlation-based and parameter-based MASEM), and propose some practical guidelines. Future directions for utilizing MASEM for reliability generalization are discussed. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

中文翻译：

---

可靠性系数元分析结构方程建模教程。

报告从量表或测试中获得的分数的可靠性是心理学经验研究的标准内容的一部分。由于可靠性是心理测量学中的一个关键概念，研究人员对评估跨研究的可靠性系数越来越感兴趣，并最终量化和解释可能的研究间差异。这种方法——通常称为“可靠性概括”——可以在荟萃分析的框架内指定。然而，现有的可靠性概括程序有几个方法论问题： (a) 对作为可靠性系数基础的测量模型的不切实际且通常未经检验的假设（例如，Cronbach α 的基本 τ 等价）；(b) 使用单变量方法来综合总分和子量表分数的可靠性；(c) 不同类型的可靠性系数之间缺乏可比性。然而，这些问题可以通过元分析结构方程建模 (MASEM) 直接解决，该方法通过综合研究中的相关矩阵或模型参数，将元分析与结构方程建模相结合。本文的主要目的是展示 MASEM 对可靠性系数的荟萃分析的潜力。我们回顾了有关使用可靠性泛化的现有文献，讨论和说明了两种 MASEM 方法（即基于相关性和基于参数的 MASEM），并提出了一些实用指南。讨论了利用 MASEM 进行可靠性概括的未来方向。（PsycINFO 数据库记录 (c) 2020 APA，保留所有权利）。