plot.nma {MBNMAdose} | R Documentation |
Run an NMA model
Description
Used for calculating treatment-level NMA results, either when comparing MBNMA models to models that
make no assumptions regarding dose-response , or to estimate split results for overlay.split
.
Results can also be compared between consistency (UME=FALSE
) and inconsistency
(UME=TRUE
) models to test the validity of the consistency assumption at the treatment-level.
Usage
## S3 method for class 'nma'
plot(x, bydose = TRUE, scales = "free_x", ...)
nma.run(
network,
method = "common",
likelihood = NULL,
link = NULL,
priors = NULL,
sdscale = FALSE,
warn.rhat = TRUE,
n.iter = 20000,
drop.discon = TRUE,
UME = FALSE,
pd = "pd.kl",
parameters.to.save = NULL,
...
)
Arguments
x |
An object of |
bydose |
A boolean object indicating whether to plot responses with dose
on the x-axis ( |
scales |
Should scales be fixed ( |
... |
Arguments to be sent to |
network |
An object of class |
method |
Indicates the type of split (treatment-level) NMA to perform when |
likelihood |
A string indicating the likelihood to use in the model. Can take either |
link |
A string indicating the link function to use in the model. Can take any link function
defined within JAGS (e.g. |
priors |
A named list of parameter values (without indices) and replacement prior distribution values given as strings using distributions as specified in JAGS syntax (see Plummer (2017)). Note that normal distributions in JAGS are specified as
, where
. |
sdscale |
Logical object to indicate whether to write a model that specifies a reference SD
for standardising when modelling using Standardised Mean Differences. Specifying |
warn.rhat |
A boolean object to indicate whether to return a warning if Rhat values for any monitored parameter are >1.02 (suggestive of non-convergence). |
n.iter |
number of total iterations per chain (including burn in; default: 20000) |
drop.discon |
A boolean object that indicates whether or not to drop disconnected studies from the network. |
UME |
A boolean object to indicate whether to fit an Unrelated Mean Effects model that does not assume consistency and so can be used to test if the consistency assumption is valid. |
pd |
Can take either:
|
parameters.to.save |
A character vector containing names of parameters to monitor in JAGS |
Functions
-
plot(nma)
: Plot outputs from treatment-level NMA modelsResults can be plotted either as a single forest plot, or facetted by agent and plotted with increasing dose in order to identify potential dose-response relationships. If Placebo (or any agents with dose=0) is included in the network then this will be used as the reference treatment, but if it is not then results will be plotted versus the network reference used in the NMA object (
x
).
Examples
# Run random effects NMA on the alogliptin dataset
alognet <- mbnma.network(alog_pcfb)
nma <- nma.run(alognet, method="random")
print(nma)
plot(nma)
# Run common effects NMA keeping treatments that are disconnected in the NMA
goutnet <- mbnma.network(gout)
nma <- nma.run(goutnet, method="common", drop.discon=FALSE)
# Run an Unrelated Mean Effects (UME) inconsistency model on triptans dataset
tripnet <- mbnma.network(triptans)
ume <- nma.run(tripnet, method="random", UME=TRUE)