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Current use of effect size or confidence interval analyses in clinical and biomedical research
The isolated use of the statistical hypothesis testing for two group comparison has limitations, and its combination with effect size or confidence interval analysis as complementary statistical tests is recommended. In the present work, we estimate the use of these complementary statistical tests (...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8449212/ https://www.ncbi.nlm.nih.gov/pubmed/34565930 http://dx.doi.org/10.1007/s11192-021-04150-3 |
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author | Amaral, Emilyane de Oliveira Santana Line, Sergio Roberto Peres |
author_facet | Amaral, Emilyane de Oliveira Santana Line, Sergio Roberto Peres |
author_sort | Amaral, Emilyane de Oliveira Santana |
collection | PubMed |
description | The isolated use of the statistical hypothesis testing for two group comparison has limitations, and its combination with effect size or confidence interval analysis as complementary statistical tests is recommended. In the present work, we estimate the use of these complementary statistical tests (i.e. effect size or confidence interval) in recently published in research articles in clinical and biomedical areas. Methods: The ProQuest database was used to search published studies in academic journals between 2019 and 2020. The analysis was carried out using terms that represent five areas of clinical and biomedical research: “brain”, “liver”, “heart”, “dental”, and “covid-19”. A total of 119,558 published articles were retrieved. Results: The relative use of complementary statistical tests in clinical and biomedical publications was low. The highest frequency usage of complementary statistical tests was among articles that also used statistical hypothesis testing for two-sample comparison. Publications with the term “covid-19” showed the lowest usage rate of complementary statistical tests when all article were analyzed but presented the highest rate among articles that used hypothesis testing. Conclusion: The low use of effect size or confidence interval in two-sample comparison suggests that coordinate measures should be taken in order to increase the use of this analysis in clinical and biomedical research. Their use should be emphasized in statistical disciplines for college and graduate students, become a routine procedure in research laboratories, and recommended by reviewers and editors of scientific journals. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11192-021-04150-3. |
format | Online Article Text |
id | pubmed-8449212 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-84492122021-09-20 Current use of effect size or confidence interval analyses in clinical and biomedical research Amaral, Emilyane de Oliveira Santana Line, Sergio Roberto Peres Scientometrics Article The isolated use of the statistical hypothesis testing for two group comparison has limitations, and its combination with effect size or confidence interval analysis as complementary statistical tests is recommended. In the present work, we estimate the use of these complementary statistical tests (i.e. effect size or confidence interval) in recently published in research articles in clinical and biomedical areas. Methods: The ProQuest database was used to search published studies in academic journals between 2019 and 2020. The analysis was carried out using terms that represent five areas of clinical and biomedical research: “brain”, “liver”, “heart”, “dental”, and “covid-19”. A total of 119,558 published articles were retrieved. Results: The relative use of complementary statistical tests in clinical and biomedical publications was low. The highest frequency usage of complementary statistical tests was among articles that also used statistical hypothesis testing for two-sample comparison. Publications with the term “covid-19” showed the lowest usage rate of complementary statistical tests when all article were analyzed but presented the highest rate among articles that used hypothesis testing. Conclusion: The low use of effect size or confidence interval in two-sample comparison suggests that coordinate measures should be taken in order to increase the use of this analysis in clinical and biomedical research. Their use should be emphasized in statistical disciplines for college and graduate students, become a routine procedure in research laboratories, and recommended by reviewers and editors of scientific journals. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11192-021-04150-3. Springer International Publishing 2021-09-18 2021 /pmc/articles/PMC8449212/ /pubmed/34565930 http://dx.doi.org/10.1007/s11192-021-04150-3 Text en © Akadémiai Kiadó, Budapest, Hungary 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Amaral, Emilyane de Oliveira Santana Line, Sergio Roberto Peres Current use of effect size or confidence interval analyses in clinical and biomedical research |
title | Current use of effect size or confidence interval analyses in clinical and biomedical research |
title_full | Current use of effect size or confidence interval analyses in clinical and biomedical research |
title_fullStr | Current use of effect size or confidence interval analyses in clinical and biomedical research |
title_full_unstemmed | Current use of effect size or confidence interval analyses in clinical and biomedical research |
title_short | Current use of effect size or confidence interval analyses in clinical and biomedical research |
title_sort | current use of effect size or confidence interval analyses in clinical and biomedical research |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8449212/ https://www.ncbi.nlm.nih.gov/pubmed/34565930 http://dx.doi.org/10.1007/s11192-021-04150-3 |
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