Reference
Katherine S Button, John P A Ioannidis, Claire Mokrysz, Brian A Nosek, Jonathan Flint, Emma S J Robinson, Marcus R Munafò “Power failure: why small sample size undermines the reliability of neuroscience” (2013) // Nature Reviews Neuroscience. Publisher: Springer Science and Business Media LLC. Vol. 14. No 5. Pp. 365–376. DOI: 10.1038/nrn3475
Bib
@Article{button2013,
title = {Power failure: why small sample size undermines the reliability of neuroscience},
volume = {14},
issn = {1471-0048},
url = {http://dx.doi.org/10.1038/nrn3475},
doi = {10.1038/nrn3475},
number = {5},
journal = {Nature Reviews Neuroscience},
publisher = {Springer Science and Business Media LLC},
author = {Button, Katherine S and Ioannidis, John P A and Mokrysz, Claire and Nosek, Brian A and Flint, Jonathan and Robinson, Emma S J and Munafò, Marcus R},
year = {2013},
month = {apr},
pages = {365–376}
}
Quotes (1)
The Neuroscience of Low Statistical Power
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.