New research has questioned the reliability of neuroscience studies, saying
> that conclusions could be misleading due to small sample sizes.
> A team led by academics from the University of Bristol reviewed 48
> articles on neuroscience meta-analysis which were published in 2011 and
> concluded that most had an average power of around 20 per cent – a finding
> which means the chance of the average study discovering the effect being
> investigated is only one in five.
> The paper, being published in Nature Reviews
> Neuroscience<http://www.nature.com/nrn/index.html>today [10 April], reveals
> that small, low-powered studies are ‘endemic’ in
> neuroscience, producing unreliable research which is inefficient and
> It focuses on how low statistical power – caused by low sample size of
> studies, small effects being investigated, or both – can be misleading and
> produce more false scientific claims than high-powered studies.
> It also illustrates how low power reduces a study’s ability to detect any
> effects and shows that when discoveries are claimed, they are more likely
> to be false or misleading.
> The paper claims there is substantial evidence that a large proportion of
> research published in scientific literature may be unreliable as a
> Another consequence is that the findings are overestimated because smaller
> studies consistently give more positive results than larger studies. This
> was found to be the case for studies using a diverse range of methods,
> including brain imaging, genetics and animal studies.
> from the School of Social and Community Medicine, and Marcus
> from the School of Experimental Psychology, led a team of researchers from
> Stanford University, the University of Virginia and the University of
> She said: “There's a lot of interest at the moment in improving the
> reliability of science. We looked at neuroscience literature and found
> that, on average, studies had only around a 20 per cent chance of detecting
> the effects they were investigating, even if the effects are real. This has
> two important implications - many studies lack the ability to give
> definitive answers to the questions they are testing, and many claimed
> findings are likely to be incorrect or unreliable.”
> The study concludes that improving the standard of results in
> neuroscience, and enabling them to be more easily reproduced, is a key
> priority and requires attention to well-established methodological
> It recommends that existing scientific practices can be improved with
> small changes or additions to methodologies, such as acknowledging any
> limitations in the interpretation of results; disclosing methods and
> findings transparently; and working collaboratively to increase the total
> sample size and power.
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