Handling missing continuous outcome data in a Bayesian network meta-analysis
Background: A Bayesian network meta-analysis (NMA) model is a statistical method aimed at estimating the relative effects of multiple interventions against the same disease. The method has recently gained prominence, leading to the synthesis of the evidence regarding rank probabilities for each trea...
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| Main Authors: | Danila Azzolina, Ileana Baldi, Clara Minto, Daniele Bottigliengo, Giulia Lorenzoni, Dario Gregori |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Milano University Press
2018-12-01
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| Series: | Epidemiology, Biostatistics and Public Health |
| Online Access: | https://ebph.it/article/view/12985 |
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