Dien Joseph
Maryland Neuroimaging Center, University of Maryland, 8077 Greenmead, College Park, MD 20742, United States.
Int J Psychophysiol. 2017 Jan;111:42-56. doi: 10.1016/j.ijpsycho.2016.09.006. Epub 2016 Sep 10.
Analysis of variance (ANOVA) is a fundamental procedure for event-related potential (ERP) research and yet there is very little guidance for best practices. It is important for the field to develop evidence-based best practices: 1) to minimize the Type II error rate by maximizing statistical power, 2) to minimize the Type I error rate by reducing the latitude for varying procedures, and 3) to identify areas for further methodological improvements. While generic treatments of ANOVA methodology are available, ERP datasets have many unique characteristics that must be considered. In the present report, a novelty oddball dataset was utilized as a test case to determine whether three aspects of ANOVA procedures as applied to ERPs make a real-world difference: the effects of reference site, regional channels, and robust ANOVAs. Recommendations are provided for best practices in each of these areas.
方差分析（ANOVA）是事件相关电位（ERP）研究的基本方法，但关于最佳实践的指导却非常少。该领域制定基于证据的最佳实践很重要：1）通过最大化统计功效来最小化II类错误率；2）通过减少不同程序的变化范围来最小化I类错误率；3）识别进一步方法改进的领域。虽然有通用的方差分析方法论述，但ERP数据集有许多必须考虑的独特特征。在本报告中，一个新颖的Oddball数据集被用作测试案例，以确定应用于ERP的方差分析程序的三个方面在实际中是否有差异：参考位点、区域通道和稳健方差分析的影响。针对这些领域的每一个都提供了最佳实践建议。
