netgraph.crossnma {crossnma}R Documentation

Produce a network plot

Description

Create a network plot of the cross network meta-analysis or meta-regression

Usage

## S3 method for class 'crossnma'
netgraph(x, ...)

Arguments

x

An object produced by crossnma.

...

... Additional arguments (passed on to netgraph.netmeta)

Value

A data frame containing the following columns:

labels

Treatment labels.

seq

Sequence of treatment labels.

xpos

Position of treatment / edge on x-axis.

ypos

Position of treatment / edge on y-axis.

zpos

Position of treatment / edge on z-axis (for 3-D plots).

xpos.labels

Position of treatment labels on x-axis (for 2-D plots).

ypos.labels

Position of treatment labels on y-axis (for 2-D plots).

adj.x

Adjustment for treatment label on x-axis.

adj.y

Adjustment for treatment label on y-axis.

adj.z

Adjustment for treatment label on z-axis (for 3-D plots).

Author(s)

Tasnim Hamza tasnim.hamza@ispm.unibe.ch

See Also

netgraph.netmeta

Examples

# We conduct a network meta-analysis assuming a random-effects
# model.
# The data comes from randomized-controlled trials and
# non-randomized studies (combined naively)
head(ipddata) # participant-level data
head(stddata) # study-level data

# Create a JAGS model
mod <- crossnma.model(treat, id, relapse, n, design,
  prt.data = ipddata, std.data = stddata,
  reference = "A", trt.effect = "random", method.bias = "naive")

# Fit JAGS model
# (suppress warning 'Adaptation incomplete' due to n.adapt = 20)
fit <-
  suppressWarnings(crossnma(mod, n.adapt = 20,
    n.iter = 50, thin = 1, n.chains = 3))

# Create network plot
netgraph(fit)


[Package crossnma version 1.0.1 Index]