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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...

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Autores principales: Hu, Dapeng, O'Connor, Annette M., Wang, Chong, Sargeant, Jan M., Winder, Charlotte B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
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.
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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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