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Potential Reporting Bias in fMRI Studies of the Brain

Author

Listed:
  • Sean P David
  • Jennifer J Ware
  • Isabella M Chu
  • Pooja D Loftus
  • Paolo Fusar-Poli
  • Joaquim Radua
  • Marcus R Munafò
  • John P A Ioannidis

Abstract

Background: Functional magnetic resonance imaging (fMRI) studies have reported multiple activation foci associated with a variety of conditions, stimuli or tasks. However, most of these studies used fewer than 40 participants. Methodology: After extracting data (number of subjects, condition studied, number of foci identified and threshold) from 94 brain fMRI meta-analyses (k = 1,788 unique datasets) published through December of 2011, we analyzed the correlation between individual study sample sizes and number of significant foci reported. We also performed an analysis where we evaluated each meta-analysis to test whether there was a correlation between the sample size of the meta-analysis and the number of foci that it had identified. Correlation coefficients were then combined across all meta-analyses to obtain a summary correlation coefficient with a fixed effects model and we combine correlation coefficients, using a Fisher’s z transformation. Principal Findings: There was no correlation between sample size and the number of foci reported in single studies (r = 0.0050) but there was a strong correlation between sample size and number of foci in meta-analyses (r = 0.62, p 40) numbers of foci and claimed as many discovered foci as studies with sample sizes ≥45, whereas meta-analyses yielded a limited number of foci relative to the yield that would be anticipated from smaller single studies. Conclusions: These results are consistent with possible reporting biases affecting small fMRI studies and suggest the need to promote standardized large-scale evidence in this field. It may also be that small studies may be analyzed and reported in ways that may generate a larger number of claimed foci or that small fMRI studies with inconclusive, null, or not very promising results may not be published at all.

Suggested Citation

  • Sean P David & Jennifer J Ware & Isabella M Chu & Pooja D Loftus & Paolo Fusar-Poli & Joaquim Radua & Marcus R Munafò & John P A Ioannidis, 2013. "Potential Reporting Bias in fMRI Studies of the Brain," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-9, July.
  • Handle: RePEc:plo:pone00:0070104
    DOI: 10.1371/journal.pone.0070104
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    References listed on IDEAS

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    1. Kerry Dwan & Douglas G Altman & Juan A Arnaiz & Jill Bloom & An-Wen Chan & Eugenia Cronin & Evelyne Decullier & Philippa J Easterbrook & Erik Von Elm & Carrol Gamble & Davina Ghersi & John P A Ioannid, 2008. "Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias," PLOS ONE, Public Library of Science, vol. 3(8), pages 1-31, August.
    2. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
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    1. Estelle Dumas-Mallet & Katherine Button & Thomas Boraud & Marcus Munafo & François Gonon, 2016. "Replication Validity of Initial Association Studies: A Comparison between Psychiatry, Neurology and Four Somatic Diseases," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-20, June.

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