Nature Reviews Neuroscience, advance online publication, Published online 10 April 2013| doi:10.1038/nrn3475
Power failure: why small sample size undermines the reliability of neuroscience
Katherine S. Button1,2, John P. A. Ioannidis3, Claire Mokrysz1, Brian A. Nosek4, Jonathan Flint5, Emma S. J. Robinson6 & Marcus R. Munafò1 About the authors
Link to full paper.
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.
- School of Experimental Psychology, University of Bristol, Bristol, BS8 1TU, UK.
- School of Social and Community Medicine, University of Bristol, Bristol, BS8 2BN, UK.
- Stanford University School of Medicine, Stanford, California 94305, USA.
- Department of Psychology, University of Virginia, Charlottesville, Virginia 22904, USA.
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK.
- School of Physiology and Pharmacology, University of Bristol, Bristol, BS8 1TD, UK.
Published online 10 April 2013