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Bad Stats Plague Neuroscience

A new study blames the unreliable nature of some research in the field on underpowered statistical analyses.

Written byBob Grant
| 1 min read

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An image from an fMRI study of brain activity in schizophrenia patientsWIKIMEDIA, PLOS One. 2010 AUG 11;5(8):e12068.Weak statistics are the downfall of many neuroscience studies, according to researchers that analyzed the statistical strategies employed by dozens of published reports in the field. Especially lacking in statistical power are human neuroimaging studies—especially those that use fMRI to infer brain activity—noted the coauthors of the analysis, published in Nature Reviews Neuroscience last week (April 10).

By taking a look at 49 meta-analyses published in 2011, involving a total of 730 neuroscience studies, a team of researchers from the United Kingdom and United States found that about half of the papers had a statistical power below 20 percent. Statistical power is a measure of the probability that a study will detect the presence of a true phenomenon in the samples at hand. High-powered studies can demonstrate even small effects if sample sizes are big enough. Low-powered studies, however, run the risk of either missing genuine phenomena or reporting false positives, usually due to considering too few samples. Research studies typically aim to have a statistical power of at least 80 percent.

Human neuroimaging studies had a median statistical power of just ...

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Meet the Author

  • From 2017 to 2022, Bob Grant was Editor in Chief of The Scientist, where he started in 2007 as a Staff Writer. Before joining the team, he worked as a reporter at Audubon and earned a master’s degree in science journalism from New York University. In his previous life, he pursued a career in science, getting a bachelor’s degree in wildlife biology from Montana State University and a master’s degree in marine biology from the College of Charleston in South Carolina. Bob edited Reading Frames and other sections of the magazine.

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