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CINeMA: An approach for assessing confidence in the results of a network meta-analysis
PLoS Medicine · 2020 · Vol. 17(4) · pp. e1003082–e1003082
Adriani Nikolakopoulou✉(University of Bern)Julian P. T. Higgins✉(University of Bristol)Theodoros Papakonstantinou✉(University of Bern)Anna Chaimani✉(Inserm)Cinzia Del Giovane✉(University of Bern)Matthias Egger✉(University of Bern)Georgia Salanti✉(University of Bern)
Abstract
Via 3 examples, we show that CINeMA improves transparency and avoids the selective use of evidence when forming judgments, thus limiting subjectivity in the process. CINeMA is easy to apply even in large and complicated networks.
Meta-analysis and systematic reviewsMeta-analysisMovie theaterCredibilityComputer scienceTransparency (behavior)Confidence intervalPublication biasProcess (computing)PsychologyData science
MeSH terms
Network Meta-Analysis as TopicNetwork Meta-AnalysisCoronary Artery DiseaseElectrocardiographyExercise TestHumansConfidence IntervalsRandomized Controlled Trials as TopicMagnetic Resonance Imaging, Cine
Funding
- National Science Foundation
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Citations
1,581
FWCI
115.33
field-weighted impact
References
63
Percentile
100%
vs. same field & year
Citations per year
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