dmulti

Function combines different dose-response functions together to create an object containing
parameters for multiple dose-response functions.

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.

Hugo Pedder

MBNMAdose

Dose-Response MBNMA Models

Adil Karim

dmulti function

<dl><dt>funs</dt>
<dd>A list of objects of <code>class("dosefun")</code>, each element of which corresponds to
an agent in the dataset to be modelled. The list length must be equal to the number of
agents in <code>network$agents</code> used in <code>mbnma.run()</code>, and the order of the dose-response
functions in the list is assumed to correspond to the same order of agents in <code>network$agents</code>.</dd></dl>

Arguments

Agent-specific dose-response function — dmulti

<dl>

<dt>funs</dt>
<dd>A list of objects of <code>class("dosefun")</code>, each element of which corresponds to
an agent in the dataset to be modelled. The list length must be equal to the number of
agents in <code>network$agents</code> used in <code>mbnma.run()</code>, and the order of the dose-response
functions in the list is assumed to correspond to the same order of agents in <code>network$agents</code>.</dd>

</dl>

dmulti: Agent-specific dose-response function

Description

Usage

Value

Arguments

Examples