2017/01/05 by Geoffrey J. Goodhill, Geoffrey J Goodhill, Goodhill, Geoffrey J
Biochemistry, Genetics and Molecular Biology · Mathematics · Neuroscience · #Applications (stat.AP) #Cell Image Analysis Techniques #FOS: Biological sciences #FOS: Computer and information sciences #Functional Brain Connectivity Studies #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #q-bio.NC #stat.AP
paper · pdf · doi:10.48550/arxiv.1701.01219
5 pages
arxiv created 2017/01/05 · openalex publication_date 2017/01/05 · arxiv updated 2017/01/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
It has been demonstrated that the statistical power of many neuroscience studies is very low, so that the results are unlikely to be robustly reproducible. How are neuroscientists and the journals in which they publish responding to this problem? Here I review the sample size justifications provided for all 15 papers published in one recent issue of the leading journal Nature Neuroscience. Of these, only one claimed it was adequately powered. The others mostly appealed to the sample sizes used in earlier studies, despite a lack of evidence that these earlier studies were adequately powered. Thus, concerns regarding statistical power in neuroscience have mostly not yet been addressed.