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While science as a whole has produced remarkably reliable answers to a lot of questions, it does so despite the fact that any individual study may not be reliable. Issues like small errors on the part of researchers, unidentified problems with materials or equipment, or the tendency to publish positive answers can alter the results of a single paper. But collectively, through multiple studies, science as a whole inches towards an understanding of the underlying reality.
A meta-analysis is a way to formalize that process. It takes the results of multiple studies and combines them, increasing the statistical power of the analysis. This may cause exciting results seen in a few small studies to vanish into statistical noise, or it can tease out a weak effect that's completely lost in more limited studies.
But a meta-analysis only works its magic if the underlying data is solid. And a new study that looks at multiple meta-analyses (a meta-meta-analysis?) suggests that one of those factors—our tendency to publish results that support hypotheses—is making the underlying data less solid than we like.
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