Literature DB >> 23571845

Power failure: why small sample size undermines the reliability of neuroscience.

Katherine S Button1, John P A Ioannidis, Claire Mokrysz, Brian A Nosek, Jonathan Flint, Emma S J Robinson, Marcus R Munafò.   

Abstract

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.

Mesh:

Year:  2013        PMID: 23571845     DOI: 10.1038/nrn3475

Source DB:  PubMed          Journal:  Nat Rev Neurosci        ISSN: 1471-003X            Impact factor:   34.870


  80 in total

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