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

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Network meta-analysis: application and practice using R software

Open access
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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Crossref · 10.4178/epih.e2019013

Cites

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Figures

Figure 1. Monte Carlo simulation.
Figure 1. Monte Carlo simulation.CC BY · PubMed Central
Figure 2. Overall concept of the Bayesian approach using a Markov chain Monte Carlo (MCMC) simulation.
Figure 2. Overall concept of the Bayesian approach using a Markov chain Monte Carlo (MCMC) simulation.CC BY · PubMed Central
Figure 3. Flow chart of network meta-analysis using the “gemtc” R package. MCMC, Markov chain Monte Carlo; DIC, deviance information criterion.
Figure 3. Flow chart of network meta-analysis using the “gemtc” R package. MCMC, Markov chain Monte Carlo; DIC, deviance information criterion.CC BY · PubMed Central
Figure 4. Network plot using the “gemtc” package. A: placebo; B: IV (single); C: IV (double); D: topical; E: combination. IV, intravenous injection.
Figure 4. Network plot using the “gemtc” package. A: placebo; B: IV (single); C: IV (double); D: topical; E: combination. IV, intravenous injection.CC BY · PubMed Central
Figure 5. Trace and density plots: (A) iterations=100 (left) vs. 500 (right); (B) iterations=10,000 & thin=20; (C) iterations=10,000 & thin=10.
Figure 5. Trace and density plots: (A) iterations=100 (left) vs. 500 (right); (B) iterations=10,000 & thin=20; (C) iterations=10,000 & thin=10.CC BY · PubMed Central
Figure 6. Forest plot_reference A. A: placebo; B: IV (single); C: IV (double); D: topical; E: combination. IV, intravenous; OR, odds ratio; CrI, credible interval.
Figure 6. Forest plot_reference A. A: placebo; B: IV (single); C: IV (double); D: topical; E: combination. IV, intravenous; OR, odds ratio; CrI, credible interval.CC BY · PubMed Central
Figure 7. Flow chart of network meta-analysis using the “netmeta” R package.
Figure 7. Flow chart of network meta-analysis using the “netmeta” R package.CC BY · PubMed Central

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Research works printed but not linked: 1

  1. R software “gemtc” & “netmeta” packages

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Metadata

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
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
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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