Statistics for the<i>European Respiratory Journal</i>

Chinn, Susan

doi:10.1183/09031936.01.00227001

Cited by 11 publications

(7 citation statements)

References 36 publications

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“…For comparisons of paired data within the study groups the paired t ‐test was used. According to Chinn (23) the t ‐test is preferable to the equivalent nonparametric tests as it is more powerful and robust to non‐normality. Correlations were assessed by computing Pearson correlation coefficients.…”

Section: Methodsmentioning

confidence: 99%

Surfactant protein levels in bronchoalveolar lavage after segmental allergen challenge in patients with asthma

Erpenbeck

Schmidt

Günther

et al. 2006

Allergy

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Section: Methodsmentioning

confidence: 99%

Surfactant protein levels in bronchoalveolar lavage after segmental allergen challenge in patients with asthma

Erpenbeck

Schmidt

Günther

et al. 2006

Allergy

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“…Respiratory healthcare professionals clearly recognise the importance of biostatistical and data-analytical concepts [ 6 , 7 ]. However, there has been no evaluation of which statistical methods are adopted in respiratory research papers.…”

Section: Introductionmentioning

confidence: 99%

Reporting data analysis methods in high-impact respiratory journals

2018

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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.

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“…To improve the quality of data analysis and reporting in manuscripts submitted for possible publication, the increasing number of journals have issued statistical guidelines and have also introduced the statistical editors who are responsible for statistical peer-review (2–4). …”

Section: Introductionmentioning

confidence: 99%

Practical recommendations for statistical analysis and data presentation in Biochemia Medica journal

Šimundić¹

2012

Biochem Med

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The aim of this article is to highlight practical recommendations based on our experience as reviewers and journal editors and refer to some most common mistakes in manuscripts submitted to Biochemia Medica. One of the most important parts of the article is the Abstract. Authors quite often forget that Abstract is sometimes the fi rst (and only) part of the article read by the readers. The article Abstract must therefore be comprehensive and provide key results of your work. Problematic part of the article, also often neglected by authors is the subheading Statistical analysis, within Materials and methods, where authors must explain which statistical tests were used in their data analysis and the rationale for using those tests. They also need to make sure that all tests used are listed under Statistical analysis section, as well as that all tests listed are indeed used in the study. When writing Results section there are several key points to keep in mind, such as: are results presented with adequate precision and accurately; is descriptive analysis appropriate; is the measure of confi dence provided for all estimates; if necessary and applicable, are correct statistical tests used for analysis; is P value provided for all tests, etc. Especially important is not to make any conclusions on the causal relationship unless the study is an experiment or clinical trial. We believe that the use of the proposed checklist might increase the quality of the submitted work and speed up the peer-review and publication process for published articles.

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Statistics for theEuropean Respiratory Journal

Cited by 11 publications

References 36 publications

Surfactant protein levels in bronchoalveolar lavage after segmental allergen challenge in patients with asthma

Surfactant protein levels in bronchoalveolar lavage after segmental allergen challenge in patients with asthma

Reporting data analysis methods in high-impact respiratory journals

Practical recommendations for statistical analysis and data presentation in Biochemia Medica journal

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