By now, most of our readers are aware that some fields of science have a reproducibility problem. Part of the problem, some argue, is the publishing community’s bias toward dramatic findings — namely, studies that show something has an effect on something else are more likely to be published than studies that don’t.
A thought provoking Retraction Watch reflection on what really is fuelling the amount of research misconduct and scientific bias that occurs, including questioning whether the ‘pressure to publish’ is really at fault.
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In a paper released today, researchers led by Daniele Fanelli and John Ioannidis — both at Stanford University — suggest that the so-called “pressure-to-publish” does not appear to bias studies toward larger so-called “effect sizes.” Instead, the researchers argue that other factors were a bigger source of bias than the pressure-to-publish, namely the use of small sample sizes (which could contain a skewed sample that shows stronger effects), and relegating studies with smaller effects to the “gray literature,” such as conference proceedings, PhD theses, and other less publicized formats.
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Read the rest of this discussion piece
Other items of Daniele Fanelli’s work appears in this library