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

  1. Tracey L Weissgerber

    Division of Nephrology and Hypertension, Mayo Clinic, Rochester, United States
    For correspondence
    weissgerber.tracey@mayo.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7490-2600
  2. Oscar Alejandro Garcia Valencia

    Division of Nephrology and Hypertension, Mayo Clinic, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0186-9448
  3. Vesna D Garovic

    Division of Nephrology and Hypertension, Mayo Clinic, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Natasa M Milic

    Division of Nephrology and Hypertension, Mayo Clinic, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Stacey J Winham

    Division of Nephrology and Hypertension, Mayo Clinic, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.

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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  1. Tracey L Weissgerber
  2. Oscar Alejandro Garcia Valencia
  3. Vesna D Garovic
  4. Natasa M Milic
  5. Stacey J Winham
(2018)
Meta-Research: Why we need to report more than 'Data were Analyzed by t-tests or ANOVA'
eLife 7:e36163.
https://doi.org/10.7554/eLife.36163
  1. Further reading

Further reading

    1. Medicine
    Mitsuru Sugimoto, Tadayuki Takagi ... Hiromasa Ohira
    Research Article

    Background:

    Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a severe and deadly adverse event following ERCP. The ideal method for predicting PEP risk before ERCP has yet to be identified. We aimed to establish a simple PEP risk score model (SuPER model: Support for PEP Reduction) that can be applied before ERCP.

    Methods:

    This multicenter study enrolled 2074 patients who underwent ERCP. Among them, 1037 patients each were randomly assigned to the development and validation cohorts. In the development cohort, the risk score model for predicting PEP was established via logistic regression analysis. In the validation cohort, the performance of the model was assessed.

    Results:

    In the development cohort, five PEP risk factors that could be identified before ERCP were extracted and assigned weights according to their respective regression coefficients: –2 points for pancreatic calcification, 1 point for female sex, and 2 points for intraductal papillary mucinous neoplasm, a native papilla of Vater, or the pancreatic duct procedures (treated as ‘planned pancreatic duct procedures’ for calculating the score before ERCP). The PEP occurrence rate was 0% among low-risk patients (≤0 points), 5.5% among moderate-risk patients (1–3 points), and 20.2% among high-risk patients (4–7 points). In the validation cohort, the C statistic of the risk score model was 0.71 (95% CI 0.64–0.78), which was considered acceptable. The PEP risk classification (low, moderate, and high) was a significant predictive factor for PEP that was independent of intraprocedural PEP risk factors (precut sphincterotomy and inadvertent pancreatic duct cannulation) (OR 4.2, 95% CI 2.8–6.3; p<0.01).

    Conclusions:

    The PEP risk score allows an estimation of the risk of PEP prior to ERCP, regardless of whether the patient has undergone pancreatic duct procedures. This simple risk model, consisting of only five items, may aid in predicting and explaining the risk of PEP before ERCP and in preventing PEP by allowing selection of the appropriate expert endoscopist and useful PEP prophylaxes.

    Funding:

    No external funding was received for this work.

    1. Medicine
    Yao Li, Hui Xin ... Wei Zhang
    Research Article

    Estrogen significantly impacts women’s health, and postmenopausal hypertension is a common issue characterized by blood pressure fluctuations. Current control strategies for this condition are limited in efficacy, necessitating further research into the underlying mechanisms. Although metabolomics has been applied to study various diseases, its use in understanding postmenopausal hypertension is scarce. Therefore, an ovariectomized rat model was used to simulate postmenopausal conditions. Estrogen levels, blood pressure, and aortic tissue metabolomics were analyzed. Animal models were divided into Sham, OVX, and OVX +E groups. Serum estrogen levels, blood pressure measurements, and aortic tissue metabolomics analyses were performed using radioimmunoassay, UHPLC-Q-TOF, and bioinformatics techniques. Based on the above research content, we successfully established a correlation between low estrogen levels and postmenopausal hypertension in rats. Notable differences in blood pressure parameters and aortic tissue metabolites were observed across the experimental groups. Specifically, metabolites that were differentially expressed, particularly L-alpha-aminobutyric acid (L-AABA), showed potential as a biomarker for postmenopausal hypertension, potentially exerting a protective function through macrophage activation and vascular remodeling. Enrichment analysis revealed alterations in sugar metabolism pathways, such as the Warburg effect and glycolysis, indicating their involvement in postmenopausal hypertension. Overall, this current research provides insights into the metabolic changes associated with postmenopausal hypertension, highlighting the role of L-AABA and sugar metabolism reprogramming in aortic tissue. The findings suggest a potential link between low estrogen levels, macrophage function, and vascular remodeling in the pathogenesis of postmenopausal hypertension. Further investigations are needed to validate these findings and explore their clinical implications for postmenopausal women.