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Elife. 2018 Dec 21;7. pii: e36163. doi: 10.7554/eLife.36163.

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

Author information

1
Division of Nephrology and Hypertension, Mayo Clinic, Rochester, United States.
2
QUEST, Charité - Universitätsmedizin Berlin, Berlin Institutes of Health, Berlin, Germany.
3
Department of Medical Statistics & Informatics, Medical Faculty, University of Belgrade, Belgrade, Serbia.
4
Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, United States.
#
Contributed equally

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.

KEYWORDS:

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

PMID:
30574870
PMCID:
PMC6326723
DOI:
10.7554/eLife.36163
[Indexed for MEDLINE]
Free PMC Article

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