Code for: Dealing with Dependent Effect Sizes in MASEM: A comparison of different approaches using empirical data. .

Code for MASEM and moderator analyses with the WPL-approach Code for: Stolwijk, I., Jak, S., Eichelsheim, V., & Hoeve, M. (2022). Dealing With Dependent Effect Sizes in MASEM. Zeitschrift für Psychologie, 230(1), 16-32. https://doi.org/10.1027/2151-2604/a000485 The objective of the present study was to examine whether different methods for dealing with dependency in meta-analytic structural equation modeling (MASEM) lead to different results. Four different methods for dealing with dependent effect sizes in MASEM were applied to empirical data, including: (1) ignoring dependency; (2) aggregation; (3) elimination; and (4) a multilevel approach. Random-effects two-stage structural equation modeling was conducted for each method separately, and potential moderators were examined using subgroup analysis. Results demonstrated that the different methods of dealing with dependency in MASEM lead to different results. Thus, the decision on which approach should be used in MASEM-analysis should be carefully considered. Given that the multilevel approach is the only approach that includes all available information while explicitly modeling dependency, it is currently the theoretically preferred approach for dealing with dependency in MASEM. Future research should evaluate the multilevel approach with simulated data. Suzanne Jak was supported by the Dutch Research Council with the grant VI.Vidi.201.009. unknown unknown

本代码用于采用WPL方法的元分析结构方程模型（Meta-Analytic Structural Equation Modeling，MASEM）与调节效应分析，对应文献为：Stolwijk, I., Jak, S., Eichelsheim, V. 及 Hoeve, M. (2022). 《元分析结构方程模型中相依效应量的处理》，刊载于《Zeitschrift für Psychologie》2022年第230卷第1期，第16-32页，DOI：10.1027/2151-2604/a000485。本研究旨在探讨元分析结构方程模型（MASEM）中处理相依效应量的不同方法是否会导致分析结果存在差异。研究将四种处理MASEM中相依效应量的方法应用于实证数据，具体包括：(1) 忽略相依性；(2) 数据聚合；(3) 剔除冗余数据；(4) 多层线性模型方法。针对每种方法分别开展随机效应两阶段结构方程建模，并通过亚组分析检验潜在调节变量。研究结果表明，MASEM中处理相依性的不同方法会产生截然不同的分析结果，因此在开展MASEM分析时，需审慎选择适配的分析路径。鉴于多层线性模型方法是唯一能够纳入所有可用信息并显式建模相依性的方法，其目前被视为MASEM中处理相依性的理论最优方案。未来研究可采用模拟数据对该多层线性模型方法进行验证。Suzanne Jak 受荷兰研究理事会资助，资助编号为VI.Vidi.201.009。未知 未知