Center for Mind & Brain and Department of Psychology, University of California, Davis, CA, USA.
Department of Psychology, University of California, Davis, CA, USA.
Psychophysiology. 2021 Jun;58(6):e13793. doi: 10.1111/psyp.13793. Epub 2021 Mar 29.
Event-related potentials (ERPs) can be very noisy, and yet, there is no widely accepted metric of ERP data quality. Here, we propose a universal measure of data quality for ERP research-the standardized measurement error (SME)-which is a special case of the standard error of measurement. Whereas some existing metrics provide a generic quantification of the noise level, the SME quantifies the data quality (precision) for the specific amplitude or latency value being measured in a given study (e.g., the peak latency of the P3 wave). It can be applied to virtually any value that is derived from averaged ERP waveforms, making it a universal measure of data quality. In addition, the SME quantifies the data quality for each individual participant, making it possible to identify participants with low-quality data and "bad" channels. When appropriately aggregated across individuals, SME values can be used to quantify the combined impact of the single-trial EEG noise and the number of trials being averaged together on the effect size and statistical power in a given experiment. If SME values were regularly included in published articles, researchers could identify the recording and analysis procedures that produce the highest data quality, which could ultimately lead to increased effect sizes and greater replicability across the field.
事件相关电位（ERPs）可能非常嘈杂，但目前还没有广泛接受的 ERP 数据质量度量标准。在这里，我们提出了一种通用的 ERP 研究数据质量度量标准——标准化测量误差（SME），它是测量误差标准的一个特例。虽然有些现有指标提供了噪声水平的通用量化，但 SME 量化了特定研究中正在测量的特定幅度或潜伏期值的（精度）数据质量（例如，P3 波的峰潜伏期）。它可以应用于从平均 ERP 波形中得出的几乎任何值，使其成为一种通用的数据质量度量标准。此外，SME 量化了每个个体参与者的数据质量，使得可以识别出数据质量低的参与者和“不良”通道。如果适当地在个体之间进行汇总，SME 值可用于量化单个 EEG 噪声的综合影响以及在给定实验中平均在一起的试验次数对效应大小和统计功效的影响。如果 SME 值定期包含在已发表的文章中，研究人员可以识别出产生最高数据质量的记录和分析程序，这最终可能会导致整个领域的效应量增加和可重复性提高。
