Department of Psychology, University of Texas at El Paso, El Paso, TX 79968, USA.
Department of Psychology, University of Toronto, Toronto, ON M5S, Canada.
Int J Psychophysiol. 2021 Apr;162:145-156. doi: 10.1016/j.ijpsycho.2021.02.006. Epub 2021 Feb 15.
Multilevel modeling (MLM) is becoming increasingly accessible and popular in the analysis of event-related potentials (ERPs). In this article, we review the benefits of MLM for analyzing psychophysiological data, which often contains repeated observations within participants, and introduce some of the decision-making points in the analytic process, including how to set up the data set, specify the model, conduct hypothesis tests, and visualize the model estimates. We highlight how the use of MLM can extend the types of theoretical questions that can be answered using ERPs, including investigations of how ERPs vary meaningfully across trials within a testing session. We also address reporting practices and provide tools to calculate effect sizes and simulate power curves. Ultimately, we hope this review contributes to emerging best practices for the use of MLM with psychophysiological data.
多层次建模（MLM）在事件相关电位（ERP）分析中变得越来越容易获得和流行。在本文中，我们回顾了 MLM 分析心理生理数据的好处，这些数据通常包含参与者内部的重复观察，并介绍了分析过程中的一些决策点，包括如何设置数据集、指定模型、进行假设检验以及可视化模型估计。我们强调了使用 MLM 可以扩展使用 ERP 回答的理论问题的类型，包括研究 ERP 在测试会话中的单次试验内如何有意义地变化。我们还讨论了报告实践，并提供了计算效应量和模拟功效曲线的工具。最终，我们希望本综述有助于为使用 MLM 分析心理生理数据提供新的最佳实践。
