Description Usage Arguments Details Value Methods (by generic) Examples
View source: R/inconsistency.functions.R
Splits contributions for a given set of treatment comparisons into direct and indirect evidence. A discrepancy between the two suggests that the consistency assumption required for NMA and MBNMA may violated.
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network 
An object of class 
fun 
A character vector specifying a functional form to be assigned to the
doseresponse. Options are given in 
user.fun 
A formula specifying any relationship including 
beta.1 
Refers to doseparameter(s) specified within the doseresponse function(s).
Can take either 
beta.2 
Refers to doseparameter(s) specified within the doseresponse function(s).
Can take either 
beta.3 
Refers to doseparameter(s) specified within the doseresponse function(s).
Can take either 
beta.4 
Refers to doseparameter(s) specified within the doseresponse function(s).
Can take either 
method 
Can take either 
knots 
The number/location of knots if a restricted cubic spline doseresponse function is fitted ( 
comparisons 
A matrix specifying the comparisons to be split (one row per comparison).
The matrix must have two columns indicating each treatment for each comparison. Values can
either be character (corresponding to the treatment names given in 
incldr 
A boolean object indicating whether or not to allow for indirect evidence contributions via the doseresponse relationship. This can be used when nodesplitting in doseresponse MBNMA to allow for a greater number of potential loops in which to check for consistency. 
... 
Arguments to be sent to 
x 
An object of 
plot.type 
A character string that can take the value of 
The S3 method plot()
on an nodesplit
object generates either
forest plots of posterior medians and 95\% credible intervals, or density plots
of posterior densities for direct and indirect evidence.
Plots the desired graph(s) and returns an object (or list of object if
plot.type=NULL
) of class(c("gg", "ggplot"))
plot
: Plot outputs from treatmentlevel nodesplit MBNMA models
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29  # Using the triptans data
network < mbnma.network(HF2PPITT)
split < mbnma.nodesplit(network, fun="emax", likelihood = "binomial", link="logit",
method="common")
#### To perform nodesplit on selected comparisons ####
# Check for closed loops of treatments with independent evidence sources
# Including indirect evidence via the doseresponse relationship
loops < inconsistency.loops(network$data.ab, incldr=TRUE)
# This...
single.split < mbnma.nodesplit(network, fun="exponential", likelihood = "binomial", link="logit",
method="random", comparisons=rbind(c("sumatriptan_1", "almotriptan_1")))
#...is the same as...
single.split < mbnma.nodesplit(network, fun="exponential", likelihood = "binomial", link="logit",
method="random", comparisons=rbind(c(6, 12)))
# Plot results
plot(split, plot.type="density") # Plot density plots of posterior densities
plot(split, plot.type="forest") # Plot forest plots of direct and indirect evidence
# Print and summarise results
print(split)
summary(split) # Generate a data frame of summary results

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