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2017 ; 114
(14
): 3714-3719
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Meta-assessment of bias in science
#MMPMID28320937
Fanelli D
; Costas R
; Ioannidis JP
Proc Natl Acad Sci U S A
2017[Apr]; 114
(14
): 3714-3719
PMID28320937
show ga
Numerous biases are believed to affect the scientific literature, but their
actual prevalence across disciplines is unknown. To gain a comprehensive picture
of the potential imprint of bias in science, we probed for the most commonly
postulated 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, we consistently
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. We also found at least partial confirmation of previous
evidence suggesting that US studies and early studies might report more extreme
effects, although these effects were smaller and more heterogeneously distributed
across meta-analyses and disciplines. Authors publishing at high rates and
receiving many citations were, overall, not at greater risk of bias. However,
effect sizes were likely to be overestimated by early-career researchers, those
working in small or long-distance collaborations, and those responsible for
scientific misconduct, supporting hypotheses that connect bias to situational
factors, lack of mutual control, and individual integrity. Some of these patterns
and risk factors might have modestly increased in intensity over time,
particularly in the social sciences. Our findings suggest that, besides one being
routinely cautious that published small, highly-cited, and earlier studies may
yield inflated results, the feasibility and costs of interventions to attenuate
biases in the literature might need to be discussed on a discipline-specific and
topic-specific basis.
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