Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/30531
Title: Examination of published articles with respect to statistical errors in veterinary sciences
Authors: Mankir, Seray
Uludağ Üniversitesi/Tıp Fakültesi/Biyoistatistik Anabilim Dalı.
Uludağ Üniversitesi/Veteriner Fakültesi/Biyoistatistik Anabilim Dalı.
Uludağ Üniversitesi/Sağlık Bilimleri Enstitüsü/Biyoistatistik Anabilim Dalı.
0000-0001-8052-0484
0000-0002-9634-0055
0000-0002-1953-7735
0000-0002-2382-290X
Ercan, İlker
Kaya, Mehmet Onur
Uzabacı, Ender
Can, Fatma Ezgi
Bashir, Albishir Musa
ABF-2367-2020
V-9415-2018
6603789069
56689249200
55347697800
56689608500
57193810863
Keywords: Veterinary sciences
Biostatistics
Review of article
Statistical error
Veterinary science
Manuscripts
Issue Date: 7-Dec-2016
Publisher: Sciendo
Citation: Ercan, İ. vd. (2017). ''Examination of published articles with respect to statistical errors in veterinary sciences''. Acta Veterinaria, 67(1), 33-42.
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 field 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.
URI: https://doi.org/10.1515/acve-2017-0004
https://sciendo.com/article/10.1515/acve-2017-0004
1820-7448
http://hdl.handle.net/11452/30531
ISSN: 0567-8315
Appears in Collections:Scopus
Web of Science

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