Meta-Research: Why we need to report more than 'Data were Analyzed by t-tests or ANOVA'
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: for example, 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.
Data availability
All data from the systematic review has been uploaded with the manuscript, along with the abstraction protocol.
Article and author information
Author details
Funding
American Heart Association (16GRNT30950002)
- Tracey L Weissgerber
National Center for Advancing Translational Sciences (UL1 TR000135)
- Tracey L Weissgerber
Mayo Clinic (Robert W. Fulk Career Development Award)
- Tracey L Weissgerber
National Cancer Institute (R03-CA212127)
- Stacey J Winham
Walter and Evelyn Simmers Career Development Award for Ovarian Cancer Research
- Stacey J Winham
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Weissgerber et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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