Fanelli D, Costas R, Ioannidis JP. Meta-assessment of bias in science. Proceedings of the National Academy of Science 2017;114(14):3714-3719
(doi: 10.1073/pnas.1618569114)
Actual prevalence of biases across disciplines is unknown. To gain a comprehensive picture of the potential imprint of bias in science, the authors probed for multiple bias-related patterns and risk factors in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was overall relatively small. However, it was observed a significant risk of small, early, and highly cited studies to overestimate effects and of studies not published in peer-reviewed journals to underestimate them.
http://www.pnas.org/content/114/14/3714.full
(doi: 10.1073/pnas.1618569114)
Actual prevalence of biases across disciplines is unknown. To gain a comprehensive picture of the potential imprint of bias in science, the authors probed for multiple bias-related patterns and risk factors in a large random sample of meta-analyses taken from all disciplines. The magnitude of these biases varied widely across fields and was overall relatively small. However, it was observed a significant risk of small, early, and highly cited studies to overestimate effects and of studies not published in peer-reviewed journals to underestimate them.
http://www.pnas.org/content/114/14/3714.full
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