Standardized measurement error: A universal metric of data quality for averaged event-related potentials.

ABSTRACT: 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

SUBMITTER: Luck SJ 

PROVIDER: S-EPMC8169536 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature