Pooling resources to enhance rigour in psychophysiological research: Insights from open science approaches to meta-analysis

Blair Saunders (Lead / Corresponding author), Michael Inzlicht

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
141 Downloads (Pure)


Recent years have witnessed calls for increased rigour and credibility in the cognitive and behavioural sciences, including psychophysiology. Many procedures exist to increase rigour, and among the most important is the need to increase statistical power. Achieving sufficient statistical power, however, is a considerable challenge for resource intensive methodologies, particularly for between-subjects designs. Meta-analysis is one potential solution; yet, the validity of such quantitative review is limited by potential bias in both the primary literature and in meta-analysis itself. Here, we provide a non-technical overview and evaluation of open science methods that could be adopted to increase the transparency of novel meta-analyses. We also contrast post hoc statistical procedures that can be used to correct for publication bias in the primary literature. We suggest that traditional meta-analyses, as applied in ERP research, are exploratory in nature, providing a range of plausible effect sizes without necessarily having the ability to confirm (or disconfirm) existing hypotheses. To complement traditional approaches, we detail how prospective meta-analyses, combined with multisite collaboration, could be used to conduct statistically powerful, confirmatory ERP research.
Original languageEnglish
Pages (from-to)112-120
Number of pages9
JournalInternational Journal of Psychophysiology
Early online date30 Jan 2021
Publication statusPublished - Apr 2021


  • open-science
  • meta-analysis
  • statistical power
  • ERPs
  • cognitive neuroscience
  • Cognitive neuroscience
  • Open-science
  • Statistical power
  • Meta-analysis

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Physiology (medical)
  • Neuroscience(all)


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