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GetReal in network meta-analysis: a review of the methodology
Open accessAbstract
Pairwise meta‐analysis is an established statistical tool for synthesizing evidence from multiple trials, but it is informative only about the relative efficacy of two specific interventions. The usefulness of pairwise meta‐analysis is thus limited in real‐life medical practice, where many competing interventions may be available for a certain condition and studies informing some of the pairwise comparisons may be lacking. This commonly encountered scenario has led to the development of network meta‐analysis (NMA). In the last decade, several applications, methodological developments, and empirical studies in NMA have been published, and the area is thriving as its relevance to public health is increasingly recognized. This article presents a review of the relevant literature on NMA methodology aiming to pinpoint the developments that have appeared in the field. Copyright © 2016 John Wiley & Sons, Ltd.
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“This approach follows the hierarchical Bayesian framework for network meta-analysis described by Lu and Ades (2004) and Dias et al. (2013), which allows continuous outcomes, including standardized mean differences, to be modeled at the arm level using a normal likelihood [37, 38].”
From The Effect of Different Psychological Interventions on Athletes' Competitive Anxiety: A Systematic Review and Bayesian Network Meta-Analysis. (2026) · cites this paper as [37]
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Self-citationPredictive P-score for treatment ranking in Bayesian network meta-analysis
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Metadata
- Authors
- Efthimiou, O., Debray, T. P. A., van Valkenhoef, G., Trelle, S., Panayidou, K., Moons, K. G. M., Reitsma, J. B., Shang, A., Salanti, G., & on behalf of GetReal Methods Review Group
- Affiliations
- University of Ioannina (GR)
- University Medical Center Utrecht (NL)
- Department of Epidemiology University of Groningen, University Medical Center Groningen Groningen The Netherlands
- University of Bern (CH)
- F. Hoffmann-La Roche AG (CH)
- Corresponding author
- Efthimiou, Orestis
- ORCID
- Venue
- Research Synthesis Methods
- Publisher
- Wiley
- Published
- 2016-01-11
- Volume
- 7
- Issue
- 3
- Pages
- 236-263
- ISSN
- 1759-2879 (ISSN-L)
- 1759-2887
- OpenAlex
- W2237437504
- Semantic Scholar
- 5a3c19f9f2a50dce244ece8903463aa0b3cd9464
- Cited by
- 401
- References
- 187
- Citations by year
- 2026: 30 · 2025: 55 · 2024: 57 · 2023: 56 · 2022: 47 · 2021: 37 · 2020: 35 · 2019: 26 · 2018: 28 · 2017: 17 · 2016: 10
- FWCI
- 9.22
- Type
- journal article
- Language
- en
- Open access
- green
- pure.amsterdamumc.nl
- Licence
- Locations
- Research Synthesis Methods (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- BORIS (University Library Bern) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
- Utrecht University Repository (Utrecht University) (submittedVersion)
- Open Access CRIS of the University of Bern
- Funders
- Innovative Medicines Initiative Joint Undertaking (115546)
- European Union's Seventh Framework Programme (FP7/2007-2013)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Social Sciences › Sociology and Political Science › Delphi Technique in Research
- Keywords
- network meta-analysis, comparative effectiveness, evidence synthesis, method development
- MeSH terms
- Network Meta-Analysis as Topic, Clinical Trials as Topic, Computer Simulation, Humans, Placebos, Regression Analysis, Research Design, Software, Statistics as Topic, Models, Statistical, Databases, Bibliographic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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