University of Notre Dame, South Bend, IN, USA.
Nanjing University of Posts and Telecommunications, Nanjing, China.
Behav Res Methods. 2024 Sep;56(6):6130-6149. doi: 10.3758/s13428-024-02342-2. Epub 2024 Feb 2.
Conditional process models, including moderated mediation models and mediated moderation models, are widely used in behavioral science research. However, few studies have examined approaches to conduct statistical power analysis for such models and there is also a lack of software packages that provide such power analysis functionalities. In this paper, we introduce new simulation-based methods for power analysis of conditional process models with a focus on moderated mediation models. These simulation-based methods provide intuitive ways for sample-size planning based on regression coefficients in a moderated mediation model as well as selected variance and covariance components. We demonstrate how the methods can be applied to five commonly used moderated mediation models using a simulation study, and we also assess the performance of the methods through the five models. We implement our approaches in the WebPower R package and also in Web apps to ease their application.
条件过程模型，包括中介调节模型和调节中介模型，在行为科学研究中被广泛应用。然而，很少有研究探讨如何对这些模型进行统计功效分析，也缺乏提供此类功效分析功能的软件包。在本文中，我们介绍了新的基于模拟的方法，用于具有中介调节模型的条件过程模型的功效分析。这些基于模拟的方法为基于中介调节模型中的回归系数以及选择的方差和协方差分量的样本量规划提供了直观的方法。我们通过模拟研究展示了如何将这些方法应用于五种常用的中介调节模型，并且还通过这五个模型评估了这些方法的性能。我们将我们的方法实现在 WebPower R 包和 Web 应用程序中，以方便应用。
