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.
|Author||Hugo Pedder [aut, cre], David Mawdsley [rev], Nicky Welton [rev], Sofia Dias [rev], Meg Bennetts [rev], Martin Boucher [rev], Adil Karim [ctb]|
|Maintainer||Hugo Pedder <[email protected]>|
|Package repository||View on CRAN|
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