Cited by 483Meta-analysis and systematic reviewsStatistical Methods and Bayesian InferenceStatistical Methods in Clinical Trials

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Network meta-analysis: application and practice using R software

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Shim, Sung Ryul, Kim, Seong-Jang, Lee, Jonghoo, Rücker, Gerta·2019·Epidemiology and Health

DOI 10.4178/epih.e2019013PMC PMC6635665

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Abstract

The objective of this study is to describe the general approaches to network meta-analysis that are available for quantitative data synthesis using R software. We conducted a network meta-analysis using two approaches: Bayesian and frequentist methods. The corresponding R packages were "gemtc" for the Bayesian approach and "netmeta" for the frequentist approach. In estimating a network meta-analysis model using a Bayesian framework, the "rjags" package is a common tool. "rjags" implements Markov chain Monte Carlo simulation with a graphical output. The estimated overall effect sizes, test for heterogeneity, moderator effects, and publication bias were reported using R software. The authors focus on two flexible models, Bayesian and frequentist, to determine overall effect sizes in network meta-analysis. This study focused on the practical methods of network meta-analysis rather than theoretical concepts, making the material easy to understand for Korean researchers who did not major in statistics. The authors hope that this study will help many Korean researchers to perform network meta-analyses and conduct related research more easily with R software.

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Network Meta-analysis
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Authors: Shim, S. R., Kim, S.-J., Lee, J., & Rücker, G.
Affiliations: Korea University (KR)
Pusan National University Yangsan Hospital (KR)
University of Freiburg (DE)
Corresponding author: Shim, Sung Ryul
ORCID: Shim, Sung Ryul
Kim, Seong-Jang
Rücker, Gerta
Venue: Epidemiology and Health
Publisher: Korean Society of Epidemiology
Published: 2019-04-08
Volume: 41
Pages: e2019013
ISSN: 1225-3596 (ISSN-L)
2092-7193
DOI: 10.4178/epih.e2019013
PMC: PMC6635665
OpenAlex: W2939443580
Cited by: 483
References: 6
Citations by year: 2026: 58 · 2025: 97 · 2024: 104 · 2023: 69 · 2022: 85 · 2021: 49 · 2020: 20 · 2019: 1
FWCI: 25.93
Type: journal article
Language: en
Open access: diamond
doi.org
Licence: cc-by
Locations: Epidemiology and Health (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords: network meta-analysis, R software, Bayesian network meta-analysis, Markov chain Monte Carlo, heterogeneity, publication bias, moderator effects
MeSH terms: Humans, Research Design, Software, Meta-Analysis as Topic

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