Power failure: Why small sample size undermines the reliability of neuroscience

Katherine S. Button, John P A Ioannidis, Claire Mokrysz, Brian A. Nosek, Jonathan Flint, Emma S J Robinson, Marcus R. Munafò

Research output: Contribution to journalArticlepeer-review

4727 Citations (SciVal)


A study with low statistical power has a reduced chance of detecting a true effect, but it is less well appreciated that low power also reduces the likelihood that a statistically significant result reflects a true effect. Here, we show that the average statistical power of studies in the neurosciences is very low. The consequences of this include overestimates of effect size and low reproducibility of results. There are also ethical dimensions to this problem, as unreliable research is inefficient and wasteful. Improving reproducibility in neuroscience is a key priority and requires attention to well-established but often ignored methodological principles.

Original languageEnglish
Pages (from-to)365-376
Number of pages12
JournalNature Reviews Neuroscience
Issue number5
Publication statusPublished - 1 May 2013


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