Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2020
2020
Historique:
received:
16
04
2020
accepted:
14
10
2020
entrez:
21
12
2020
pubmed:
22
12
2020
medline:
12
1
2021
Statut:
epublish
Résumé
In the last decades, statistical methodology has developed rapidly, in particular in the field of regression modeling. Multivariable regression models are applied in almost all medical research projects. Therefore, the potential impact of statistical misconceptions within this field can be enormous Indeed, the current theoretical statistical knowledge is not always adequately transferred to the current practice in medical statistics. Some medical journals have identified this problem and published isolated statistical articles and even whole series thereof. In this systematic review, we aim to assess the current level of education on regression modeling that is provided to medical researchers via series of statistical articles published in medical journals. The present manuscript is a protocol for a systematic review that aims to assess which aspects of regression modeling are covered by statistical series published in medical journals that intend to train and guide applied medical researchers with limited statistical knowledge. Statistical paper series cannot easily be summarized and identified by common keywords in an electronic search engine like Scopus. We therefore identified series by a systematic request to statistical experts who are part or related to the STRATOS Initiative (STRengthening Analytical Thinking for Observational Studies). Within each identified article, two raters will independently check the content of the articles with respect to a predefined list of key aspects related to regression modeling. The content analysis of the topic-relevant articles will be performed using a predefined report form to assess the content as objectively as possible. Any disputes will be resolved by a third reviewer. Summary analyses will identify potential methodological gaps and misconceptions that may have an important impact on the quality of analyses in medical research. This review will thus provide a basis for future guidance papers and tutorials in the field of regression modeling which will enable medical researchers 1) to interpret publications in a correct way, 2) to perform basic statistical analyses in a correct way and 3) to identify situations when the help of a statistical expert is required.
Identifiants
pubmed: 33347441
doi: 10.1371/journal.pone.0241427
pii: PONE-D-20-10972
pmc: PMC7751867
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0241427Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
Diagn Progn Res. 2020 Apr 2;4:3
pubmed: 32266321
BMC Med Res Methodol. 2019 Mar 6;19(1):46
pubmed: 30841848
Ann Intern Med. 2009 Aug 18;151(4):W65-94
pubmed: 19622512
PLoS Med. 2012;9(5):1-12
pubmed: 22629234
BMJ Open. 2018 May 5;8(5):e021129
pubmed: 29730629
Syst Rev. 2015 Jan 01;4:1
pubmed: 25554246
Stat Med. 2006 Jan 15;25(1):127-41
pubmed: 16217841
Transpl Int. 2017 Jan;30(1):6-10
pubmed: 27896874
Biom J. 2018 May;60(3):431-449
pubmed: 29292533
J Adv Nurs. 1997 Oct;26(4):790-7
pubmed: 9354993
Stat Med. 2014 Dec 30;33(30):5413-32
pubmed: 25074480
J Clin Epidemiol. 1996 Aug;49(8):907-16
pubmed: 8699212