The purpose of this study is to propose a decomposed-first strategy for multilevel moderated mediation and to compare the performance of three moderated mediation approaches in multilevel structural equation modeling. The following approaches were compared in simulations to test coefficients that were decomposed level by level: orthogonal partitioning with centering within cluster, random coefficient prediction, and latent moderated structural equations. The manipulated conditions for the simulation analysis were the analysis method, the number of groups, group size, and intraclass correlation. The results showed that, for samples consisting of a large number of groups, a large average group size and a large intraclass correlation, LMS had the strongest performance. This study is meaningful in that it produces interpretable coefficients by applying a decomposed-first strategy in multilevel moderated mediation and extends a basic moderated mediation model to include more specific research questions in multilevel structural equation modeling.

中文翻译：

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多级调解调解的比较方法：分解优先策略

本研究的目的是提出一种多级调节中介的分解优先策略，并比较三种调节中介方法在多级结构方程建模中的性能。在模拟中将以下方法与逐级分解的测试系数进行了比较：以集群为中心的正交分区、随机系数预测和潜在的缓和结构方程。模拟分析的操作条件是分析方法、组数、组大小和类内相关性。结果表明，对于包含大量组、大平均组大小和大类内相关性的样本，LMS 的性能最强。