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Estimating statistical power for ERP studies using the auditory N1, Tb, and P2 components.
Lachlan Hall1, Amy Dawel1, Lisa-Marie Greenwood1
1Research School of Psychology, Australian National University, Canberra, Australia.
Psychophysiology
|June 29, 2023
Summary
Statistical power in event-related potential (ERP) studies increases with more trials, participants, and effect size. Within-subject designs are more powerful than between-subject designs, requiring fewer participants and trials.
Area of Science:
- Neuroscience
- Cognitive Science
- Psychology
Background:
- Event-related potentials (ERPs), including N1, Tb, and P2 components, are crucial for understanding auditory processing.
- Current event-related potential research lacks standardized guidelines for determining adequate statistical power.
Purpose of the Study:
- To investigate the impact of trial count, participant numbers, effect magnitude, and study design on statistical power in ERP research.
- To provide data-driven recommendations for designing robust and reproducible ERP experiments.
Main Methods:
- Utilized Monte Carlo simulations to model ERP data from a passive listening task.
- Conducted 58,900 unique simulated experiments, each repeated 1,000 times, to assess statistical power under varying conditions.
Main Results:
- Statistical power positively correlated with the number of trials, participants, and effect magnitude.
- Increasing trials significantly boosted power in within-subject designs more than in between-subject designs.
- Within-subject designs achieved equivalent statistical power with fewer trials and participants compared to between-subject designs.
Conclusions:
- Careful consideration of design factors (trials, participants, effect size, design type) is essential for appropriate ERP study power.
- An online statistical power calculator has been developed to aid researchers in estimating power and designing future studies.
