ArticlePsychophysiology2021
Standardized measurement error: A universal metric of data quality for averaged event-related potentials.
Article in Psychophysiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 1 of them a synthesis that pooled it.
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Who cites it
90 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Event-related potentials in the "Triangle" framework of reading and developmental dyslexia: a systematic review.Annals of dyslexia · 2026Pooled it
- Influence of acculturation on the ERP correlates of self- and other-referencing.Cognitive, affective & behavioral neuroscience · 2026Article
- Characterizing neural indices of cognitive control in young children: A school-based ERP study with naturalistic stimuli.Developmental cognitive neuroscience · 2026Article
- Electrophysiological Correlates of Encoding Indicate Altered Processing but Comparable Subsequent Memory Effects Across Virtual Reality and Desktop-Based Conditions.The European journal of neuroscience · 2026Article
- Mind the Cap: Inclusivity Gaps in EEG Research.Psychophysiology · 2026Article
- Inclusive mobile brain-body imaging achieves equivalent EEG data quality across racial groups.PLOS digital health · 2026Article
- Reliability and statistical power: Conceptual background and practical implications.Behavior research methods · 2026Review
- The effect of working memory load on selective attention towards threatening faces in socially anxious individuals: Behavioural and electrophysiological evidence.Cognitive, affective & behavioral neuroscience · 2026Article
- Modulations of the P3b effect as a function of bilingual language experience.Scientific reports · 2026Article
- Beyond classical metrics: Generalizability theory across psychophysiological modalities.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2026Review
- Corollary discharge dysfunction in auditory verbal hallucinations: N100 suppression measured with semi-dry electrodes.Clinical neurophysiology practice · 2026Article
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- An Electroencephalographic Investigation of the Impact of Eye Movements in a Memory Probe Task.Psychophysiology · 2026Article
- Taste matters: lessons learned in translating a conditioned drug cue reactivity paradigm from rodents to humans.Frontiers in psychology · 2026Article
- Reward positivity and affective functioning in early childhood: evidence from temporospatial principal components analysis.Frontiers in human neuroscience · 2026Article
- Exploring Brain Dynamics Within the Approach-Avoidance Bias.Brain sciences · 2025Article
- Neural evidence for attentional resource allocation to postural control using brain-body imaging.Behavioural brain research · 2025Article
- The Temporal Dynamics of Attention to Threat and GAD Symptoms: A Study of LPP Slopes.Psychophysiology · 2025Article
- Right but Still Lousy: Correct Responses With an Unfavorable Outcome Elicit an Error Positivity.Psychophysiology · 2025Article
- Assessing the impact of artifact correction and artifact rejection on the performance of SVM- and LDA-based decoding of EEG signals.NeuroImage · 2025Article
30 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
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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 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.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.