Examination of published articles with respect to statistical errors in veterinary sciences

Abstract

The aim of this present work was to examine statistical errors in published veterinary science articles. A total of 204 published articles (SCI or SCI-Exp) were used in this study. The articles were chosen from among those indexed in PubMed database between the years 2010 and 2014, inclusive. A total of 199 articles had at least one statistical error. The most frequently encountered statistical error among the articles published in journals indexed in SCI and in SCI-E was "errors in summarizing data". No statistical error was found in 2.45% (n=5) of 204 (SCI: 0.98% (1/102), SCI-E: 3.92% (4/102)) articles. To reduce and prevent statistical errors in publications, the researchers must have a basic knowledge of statistics and during the study process they must consult fi eld experts. While reviewing, the reviewers have to redirect the publications to statistical editors when needed and most importantly during the process of editing, the editors have to direct the publications to a statistics reviewer.

Statistical Reporting in Nursing Research: Addressing a Common Error in Reporting of p Values (p = .000)

“…Despite increasing concern about the importance of the correct use of statistical science, our findings showed that the incorrect representation of p values (p = .000) is still common in nursing journals. However, our study found that the rate of incorrect reporting of P values was 12.8% in nursing journals, which is lower compared with previous findings, with rates of 42.04%, 18.43%, and 37.25% in radiology journals, medical journals, and veterinary journals, respectively (Ercan et al, 2015;Ercan et al, 2017;Gunel Karadeniz et al, 2019). These differences may be due to the different categories of journals and different data extraction methods.…”

“…However, despite these efforts, articles with inappropriate representation of p values continue to pass peer review and editorial scrutiny and to be published in medical journals. For example, the rate of incorrect representation of p values was 42.04% in radiology journals (Garcia‐Berthou & Alcaraz, 2004), 37.25% in veterinary journals (Ercan et al, 2017), and 18.43% in medical journals (Ercan, Karadeniz, Cangur, Ozkaya, & Demirtas, 2015). The confidence in a study will be reduced due to the incorrect representation of p values (Garcia‐Berthou & Alcaraz, 2004).…”

Excavating FAIR Data: the Case of the Multicenter Animal Spinal Cord Injury Study (MASCIS), Blood Pressure, and Neuro-Recovery

“…At the current time it remains unclear to what extent systematic reviews and meta-analyses can be relied upon to be correct reflections of raw data ( Gøtzsche et al, 2007 ) as they are based primarily on statistics reported in papers. In addition, reviews suggest that over 80% of published manuscripts in a biomedical science journal contains a least one statistical error ( Simundic & Nikolac, 2009 ), and there are no indications that statistical rigor is increasing in biomedical research ( Ercan, 2015 ; Ercan et al, 2017 ). Thus, there is much to be gained by granting the next generation of scientist’s access to FAIR datasets derived by data archeology, data recovery, and application of modern data stewardship and analytic tools of the sort applied here.…”

Issues with data and analyses: Errors, underlying themes, and potential solutions

“…Such issues are hardly new to science. Similar errors continue today, are sometimes severe enough to call entire studies into question (11), and may occur with nontrivial frequency (12)(13)(14).…”