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

The objective of the present study was to examine whether different methods for dealing with dependency in meta-analytic structural equation modelling (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 modelling 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 one that is carefully considered. Given that the multilevel approach is the only approach that includes all available information while explicitly modelling dependency, it is currently the theoretically preferred approach for dealing with dependency in MASEM. Future research should evaluate the multilevel approach with simulated data.

本研究旨在探讨处理元分析结构方程模型（MASEM）中依赖关系的不同方法是否会导致不同的结果。本研究对MASEM中处理依赖效应量所采用的四种不同方法进行了实证数据的应用，包括：（1）忽略依赖；（2）汇总；（3）消除；（4）多级方法。对每种方法分别进行了随机效应两阶段结构方程模型的构建，并通过子组分析考察了潜在的调节因素。结果表明，处理MASEM中依赖关系的不同方法会导致不同的结果。因此，在MASEM分析中选择哪种方法应经过深思熟虑。鉴于多级方法是目前唯一一种包含所有可用信息并明确建模依赖关系的途径，因此，在处理MASEM中的依赖关系时，它目前是理论上的首选方法。未来的研究应使用模拟数据对多级方法进行评估。