MBNMAdose
Dose-Response MBNMA Models
Fits Bayesian dose-response model-based network meta-analysis (MBNMA) that incorporate multiple doses within an agent by modelling different dose-response functions, as described by Mawdsley et al. (2016) doi:10.1002/psp4.12091. By modelling dose-response relationships this can connect networks of evidence that might otherwise be disconnected, and can improve precision on treatment estimates. Several common dose-response functions are provided; others may be added by the user. Various characteristics and assumptions can be flexibly added to the models, such as shared class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects models and/or by node-splitting at the treatment level.
- Version0.5.0
- R versionR (≥ 3.0.2)
- LicenseGPL-3
- Needs compilation?No
- Languageen-GB
- MBNMAdose citation info
- Last release02/07/2025
Documentation
- VignetteMBNMAdose: Checking for consistency
- VignetteMBNMAdose: Exploring the data
- VignetteMBNMAdose: Package Overview
- VignetteMBNMAdose: Perform Network Meta-Regression
- VignetteClass effect NMA analysis using MBNMAdose
- VignetteMBNMAdose outputs: Relative effects, forest plots and rankings
- VignetteMBNMAdose: Calculating model predictions
- VignetteMBNMAdose: Perform a Model-Based Network Meta-Analysis (MBNMA)
- MaterialREADME
- MaterialNEWS
- In ViewsMetaAnalysis
Team
Hugo Pedder
MaintainerShow author detailsAdil Karim
Show author detailsRolesContributor
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Dependencies
- Imports10 packages
- Suggests14 packages