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How to Conduct a Bayesian Network Meta-Analysis
Network meta-analysis is a general approach to integrate the results of multiple studies in which multiple treatments are compared, often in a pairwise manner. In this tutorial, we illustrate the procedures for conducting a network meta-analysis for binary outcomes data in the Bayesian framework usi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248597/ https://www.ncbi.nlm.nih.gov/pubmed/32509807 http://dx.doi.org/10.3389/fvets.2020.00271 |
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author | Hu, Dapeng O'Connor, Annette M. Wang, Chong Sargeant, Jan M. Winder, Charlotte B. |
author_facet | Hu, Dapeng O'Connor, Annette M. Wang, Chong Sargeant, Jan M. Winder, Charlotte B. |
author_sort | Hu, Dapeng |
collection | PubMed |
description | Network meta-analysis is a general approach to integrate the results of multiple studies in which multiple treatments are compared, often in a pairwise manner. In this tutorial, we illustrate the procedures for conducting a network meta-analysis for binary outcomes data in the Bayesian framework using example data. Our goal is to describe the workflow of such an analysis and to explain how to generate informative results such as ranking plots and treatment risk posterior distribution plots. The R code used to conduct a network meta-analysis in the Bayesian setting is provided at GitHub. |
format | Online Article Text |
id | pubmed-7248597 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72485972020-06-05 How to Conduct a Bayesian Network Meta-Analysis Hu, Dapeng O'Connor, Annette M. Wang, Chong Sargeant, Jan M. Winder, Charlotte B. Front Vet Sci Veterinary Science Network meta-analysis is a general approach to integrate the results of multiple studies in which multiple treatments are compared, often in a pairwise manner. In this tutorial, we illustrate the procedures for conducting a network meta-analysis for binary outcomes data in the Bayesian framework using example data. Our goal is to describe the workflow of such an analysis and to explain how to generate informative results such as ranking plots and treatment risk posterior distribution plots. The R code used to conduct a network meta-analysis in the Bayesian setting is provided at GitHub. Frontiers Media S.A. 2020-05-19 /pmc/articles/PMC7248597/ /pubmed/32509807 http://dx.doi.org/10.3389/fvets.2020.00271 Text en Copyright © 2020 Hu, O'Connor, Wang, Sargeant and Winder. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Veterinary Science Hu, Dapeng O'Connor, Annette M. Wang, Chong Sargeant, Jan M. Winder, Charlotte B. How to Conduct a Bayesian Network Meta-Analysis |
title | How to Conduct a Bayesian Network Meta-Analysis |
title_full | How to Conduct a Bayesian Network Meta-Analysis |
title_fullStr | How to Conduct a Bayesian Network Meta-Analysis |
title_full_unstemmed | How to Conduct a Bayesian Network Meta-Analysis |
title_short | How to Conduct a Bayesian Network Meta-Analysis |
title_sort | how to conduct a bayesian network meta-analysis |
topic | Veterinary Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7248597/ https://www.ncbi.nlm.nih.gov/pubmed/32509807 http://dx.doi.org/10.3389/fvets.2020.00271 |
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