Department of Psychology, Columbia University, 406 Schermerhorn Hall, 1190 Amsterdam Avenue MC 5501, New York, NY, 10027, USA.
Behav Res Methods. 2018 Oct;50(5):2125-2143. doi: 10.3758/s13428-017-0980-9.
Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and neuroscience. One reason for the scarcity of applications is that these areas of psychology commonly employ within-subjects designs, and mediation models for within-subjects data are considerably more complicated than for between-subjects data. Here, we draw attention to the importance and ubiquity of mediational hypotheses in within-subjects designs, and we present a general and flexible software package for conducting Bayesian within-subjects mediation analyses in the R programming environment. We use experimental data from cognitive psychology to illustrate the benefits of within-subject mediation for theory testing and comparison.
统计中介允许研究人员通过中介变量来研究实验操作的潜在因果效应。它是评估假设因果机制存在和强度的有力工具。尽管中介在某些心理学领域得到了应用，但在认知心理学和神经科学中却很少应用。造成应用稀缺的原因之一是这些心理学领域通常采用被试内设计，而被试内数据的中介模型比被试间数据的中介模型复杂得多。在这里，我们提请注意中介假设在被试内设计中的重要性和普遍性，并介绍了一个通用且灵活的软件包，用于在 R 编程语言环境中进行贝叶斯被试内中介分析。我们使用认知心理学的实验数据来说明被试内中介在理论检验和比较方面的好处。
