Library / High Impact = High Statistical Standards? Not Necessarily so


Patrizio E Tressoldi, David Giofré, Francesco Sella, Geoff Cumming, Hills “High Impact = High Statistical Standards? Not Necessarily So” (2013) // PLoS ONE. Publisher: Public Library of Science (PLoS). Vol. 8. No 2. Pp. e56180. DOI: 10.1371/journal.pone.0056180


  title = {High Impact = High Statistical Standards? Not Necessarily So},
  volume = {8},
  issn = {1932-6203},
  url = {},
  doi = {10.1371/journal.pone.0056180},
  number = {2},
  journal = {PLoS ONE},
  publisher = {Public Library of Science (PLoS)},
  author = {Tressoldi, Patrizio E and Giofré, David and Sella, Francesco and Cumming, Geoff},
  editor = {Hills},
  year = {2013},
  month = {feb},
  pages = {e56180}

Quotes (1)

Statistical Practices in high-impact Journals

What are the statistical practices of articles published in journals with a high impact factor? Are there differences compared with articles published in journals with a somewhat lower impact factor that have adopted editorial policies to reduce the impact of limitations of Null Hypothesis Significance Testing? To investigate these questions, the current study analyzed all articles related to psychological, neuropsychological and medical issues, published in 2011 in four journals with high impact factors: Science, Nature, The New England Journal of Medicine and The Lancet, and three journals with relatively lower impact factors: Neuropsychology, Journal of Experimental Psychology-Applied and the American Journal of Public Health. Results show that Null Hypothesis Significance Testing without any use of confidence intervals, effect size, prospective power and model estimation, is the prevalent statistical practice used in articles published in Nature, 89%, followed by articles published in Science, 42%.