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A Comparison of Multilevel Mediation Modeling Methods: Recommendations for Applied Researchers

机译:多级调解模拟方法的比较:应用研究人员的建议

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摘要

Multilevel structural equation modeling (MSEM) has been proposed as a valuable tool for estimating mediation in multilevel data and has known advantages over traditional multilevel modeling, including conflated and unconflated techniques (CMM & UMM). Recent methodological research has focused on comparing the three methods for 2-1-1 designs, but in regards to 1-1-1 mediation designs, there are significant gaps in the published literature that prevent applied researchers from making educated decisions regarding which model to employ in their own specific research design. A Monte Carlo study was performed to compare MSEM, UMM, and CMM on relative bias, confidence interval coverage, Type I Error, and power in a 1-1-1 model with random slopes under varying data conditions. Recommendations for applied researchers are discussed and an empirical example provides context for the three methods.
机译:已经提出了多级结构方程建模(MSEM)作为用于估计多级数据中的中介的有价值的工具,并且具有与传统多级建模的已知优势,包括混合和无关的技术(CMM&UMM)。 最近的方法研究专注于比较2-1-1设计的三种方法,但在1-1-1个中介设计方面,发表文献中存在显着差距,以防止应用研究人员对哪种模型做出教育的决定 采用自己的特定研究设计。 进行蒙特卡罗研究以比较MSEM,UMM和CMM对相对偏置,置信区间覆盖,I型错误和1-1-1模型中的电力,随机斜率在不同的数据条件下进行随机斜率。 讨论了应用研究人员的建议,并对三种方法提供了上下文。

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