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Reporting data analysis methods in high-impact respiratory journals
Data analysis methods play an important role in respiratory research. We evaluated the application and complexity of data analytical methods in high-impact respiratory journals and compared the statistical reporting in these respiratory articles with reports published in other eminent medical journa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Respiratory Society
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5994482/ https://www.ncbi.nlm.nih.gov/pubmed/29900177 http://dx.doi.org/10.1183/23120541.00140-2017 |
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author | Nieminen, Pentti Toljamo, Tuula Vähänikkilä, Hannu |
author_facet | Nieminen, Pentti Toljamo, Tuula Vähänikkilä, Hannu |
author_sort | Nieminen, Pentti |
collection | PubMed |
description | Data analysis methods play an important role in respiratory research. We evaluated the application and complexity of data analytical methods in high-impact respiratory journals and compared the statistical reporting in these respiratory articles with reports published in other eminent medical journals. This study involved a total of 160 papers published in 2015 in the European Respiratory Journal, American Journal of Respiratory and Critical Care Medicine, Chest and Thorax, and 680 papers published between 2007–2015 in other medical journals including the Lancet and New England Journal of Medicine. We manually reviewed the articles to determine the way in which they reported the methods applied in data analysis. The statistical intensity in the respiratory journals was equal to that in eminent medical journals. Traditional ways of testing statistical significance were widely used in respiratory articles. Statistical procedures were not always described in sufficient detail, and the prominent respiratory journals did not display different profiles with respect to their statistical content. Readers of the prominent respiratory journals need to possess a substantial level of statistical expertise if they wish to critically evaluate the design, methodology, data analysis and interpretation of the findings published in these journals. |
format | Online Article Text |
id | pubmed-5994482 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | European Respiratory Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-59944822018-06-13 Reporting data analysis methods in high-impact respiratory journals Nieminen, Pentti Toljamo, Tuula Vähänikkilä, Hannu ERJ Open Res Original Articles Data analysis methods play an important role in respiratory research. We evaluated the application and complexity of data analytical methods in high-impact respiratory journals and compared the statistical reporting in these respiratory articles with reports published in other eminent medical journals. This study involved a total of 160 papers published in 2015 in the European Respiratory Journal, American Journal of Respiratory and Critical Care Medicine, Chest and Thorax, and 680 papers published between 2007–2015 in other medical journals including the Lancet and New England Journal of Medicine. We manually reviewed the articles to determine the way in which they reported the methods applied in data analysis. The statistical intensity in the respiratory journals was equal to that in eminent medical journals. Traditional ways of testing statistical significance were widely used in respiratory articles. Statistical procedures were not always described in sufficient detail, and the prominent respiratory journals did not display different profiles with respect to their statistical content. Readers of the prominent respiratory journals need to possess a substantial level of statistical expertise if they wish to critically evaluate the design, methodology, data analysis and interpretation of the findings published in these journals. European Respiratory Society 2018-06-11 /pmc/articles/PMC5994482/ /pubmed/29900177 http://dx.doi.org/10.1183/23120541.00140-2017 Text en Copyright ©ERS 2018 http://creativecommons.org/licenses/by-nc/4.0/ This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial Licence 4.0. |
spellingShingle | Original Articles Nieminen, Pentti Toljamo, Tuula Vähänikkilä, Hannu Reporting data analysis methods in high-impact respiratory journals |
title | Reporting data analysis methods in high-impact respiratory journals |
title_full | Reporting data analysis methods in high-impact respiratory journals |
title_fullStr | Reporting data analysis methods in high-impact respiratory journals |
title_full_unstemmed | Reporting data analysis methods in high-impact respiratory journals |
title_short | Reporting data analysis methods in high-impact respiratory journals |
title_sort | reporting data analysis methods in high-impact respiratory journals |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5994482/ https://www.ncbi.nlm.nih.gov/pubmed/29900177 http://dx.doi.org/10.1183/23120541.00140-2017 |
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