Why we need to report more than 'Data were Analyzed by t-tests or ANOVA'

Tracey L. Weissgerber, Oscar Garcia-Valencia, Vesna D Garovic, Natasa M. Milic, Stacey J Winham

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Transparent reporting is essential for the critical evaluation of studies. However, the reporting of statistical methods for studies in the biomedical sciences is often limited. This systematic review examines the quality of reporting for two statistical tests, t-tests and ANOVA, for papers published in a selection of physiology journals in June 2017. Of the 328 original research articles examined, 277 (84.5%) included an ANOVA or t-test or both. However, papers in our sample were routinely missing essential information about both types of tests: 213 papers (95% of the papers that used ANOVA) did not contain the information needed to determine what type of ANOVA was performed, and 26.7% of papers did not specify what post-hoc test was performed. Most papers also omitted the information needed to verify ANOVA results. Essential information about t-tests was also missing in many papers. We conclude by discussing measures that could be taken to improve the quality of reporting.

Original languageEnglish (US)
JournaleLife
Volume7
DOIs
StatePublished - Dec 21 2018

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Keywords

  • analysis of variance
  • human biology
  • medicine
  • meta-research
  • none
  • statistics
  • systematic review
  • t-test
  • transparency

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)

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