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Bayesian Analysis Reporting Guidelines

Previous surveys of the literature have shown that reports of statistical analyses often lack important information, causing lack of transparency and failure of reproducibility. Editors and authors agree that guidelines for reporting should be encouraged. This Review presents a set of Bayesian analy...

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Autor principal: Kruschke, John K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526359/
https://www.ncbi.nlm.nih.gov/pubmed/34400814
http://dx.doi.org/10.1038/s41562-021-01177-7
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description Previous surveys of the literature have shown that reports of statistical analyses often lack important information, causing lack of transparency and failure of reproducibility. Editors and authors agree that guidelines for reporting should be encouraged. This Review presents a set of Bayesian analysis reporting guidelines (BARG). The BARG encompass the features of previous guidelines, while including many additional details for contemporary Bayesian analyses, with explanations. An extensive example of applying the BARG is presented. The BARG should be useful to researchers, authors, reviewers, editors, educators and students. Utilization, endorsement and promotion of the BARG may improve the quality, transparency and reproducibility of Bayesian analyses.
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spelling pubmed-85263592021-11-04 Bayesian Analysis Reporting Guidelines Kruschke, John K. Nat Hum Behav Review Article Previous surveys of the literature have shown that reports of statistical analyses often lack important information, causing lack of transparency and failure of reproducibility. Editors and authors agree that guidelines for reporting should be encouraged. This Review presents a set of Bayesian analysis reporting guidelines (BARG). The BARG encompass the features of previous guidelines, while including many additional details for contemporary Bayesian analyses, with explanations. An extensive example of applying the BARG is presented. The BARG should be useful to researchers, authors, reviewers, editors, educators and students. Utilization, endorsement and promotion of the BARG may improve the quality, transparency and reproducibility of Bayesian analyses. Nature Publishing Group UK 2021-08-16 2021 /pmc/articles/PMC8526359/ /pubmed/34400814 http://dx.doi.org/10.1038/s41562-021-01177-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review Article
Kruschke, John K.
Bayesian Analysis Reporting Guidelines
title Bayesian Analysis Reporting Guidelines
title_full Bayesian Analysis Reporting Guidelines
title_fullStr Bayesian Analysis Reporting Guidelines
title_full_unstemmed Bayesian Analysis Reporting Guidelines
title_short Bayesian Analysis Reporting Guidelines
title_sort bayesian analysis reporting guidelines
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526359/
https://www.ncbi.nlm.nih.gov/pubmed/34400814
http://dx.doi.org/10.1038/s41562-021-01177-7
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