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Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol

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...

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Autores principales: Bach, Paul, Wallisch, Christine, Klein, Nadja, Hafermann, Lorena, Sauerbrei, Willi, Steyerberg, Ewout W., Heinze, Georg, Rauch, Geraldine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751867/
https://www.ncbi.nlm.nih.gov/pubmed/33347441
http://dx.doi.org/10.1371/journal.pone.0241427
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author Bach, Paul
Wallisch, Christine
Klein, Nadja
Hafermann, Lorena
Sauerbrei, Willi
Steyerberg, Ewout W.
Heinze, Georg
Rauch, Geraldine
author_facet Bach, Paul
Wallisch, Christine
Klein, Nadja
Hafermann, Lorena
Sauerbrei, Willi
Steyerberg, Ewout W.
Heinze, Georg
Rauch, Geraldine
author_sort Bach, Paul
collection PubMed
description 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.
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spelling pubmed-77518672021-01-05 Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol Bach, Paul Wallisch, Christine Klein, Nadja Hafermann, Lorena Sauerbrei, Willi Steyerberg, Ewout W. Heinze, Georg Rauch, Geraldine PLoS One Registered Report Protocol 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. Public Library of Science 2020-12-21 /pmc/articles/PMC7751867/ /pubmed/33347441 http://dx.doi.org/10.1371/journal.pone.0241427 Text en © 2020 Bach et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Registered Report Protocol
Bach, Paul
Wallisch, Christine
Klein, Nadja
Hafermann, Lorena
Sauerbrei, Willi
Steyerberg, Ewout W.
Heinze, Georg
Rauch, Geraldine
Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
title Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
title_full Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
title_fullStr Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
title_full_unstemmed Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
title_short Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol
title_sort systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: study protocol
topic Registered Report Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751867/
https://www.ncbi.nlm.nih.gov/pubmed/33347441
http://dx.doi.org/10.1371/journal.pone.0241427
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