multinma (version 0.6.1)

plot.nodesplit_summary: Plots of node-splitting models

Description

Produce summary plots of node-splitting models

Usage

# S3 method for nodesplit_summary
plot(
  x,
  ...,
  pars = "d",
  stat = "dens_overlay",
  orientation = c("horizontal", "vertical", "y", "x"),
  ref_line = NA_real_
)

Value

A ggplot object.

Arguments

x

A nodesplit_summary object.

...

Additional arguments passed on to the underlying ggdist plot stat, see Details.

pars

Character vector specifying the parameters to include in the plot, choices include "d" for the direct, indirect, and network estimates of relative effects, "omega" for the inconsistency factor, and "tau" for heterogeneity standard deviation in random effects models. Default is "d".

stat

Character string specifying the ggdist plot stat to use. The default "dens_overlay" is a special case, producing an overlaid density plot.

orientation

Whether the ggdist geom is drawn horizontally ("horizontal") or vertically ("vertical"), default "horizontal".

ref_line

Numeric vector of positions for reference lines, by default no reference lines are drawn.

Details

Plotting is handled by ggplot2 and the stats and geoms provided in the ggdist package. As a result, the output is very flexible. Any plotting stats provided by ggdist may be used, via the argument stat. The default "dens_overlay" is a special exception, which uses ggplot2::geom_density(), to plot overlaid densities. Additional arguments in ... are passed to the ggdist stat, to customise the output.

Alternative stats can be specified to produce different summaries. For example, specify stat = "[half]eye" to produce (half) eye plots, or stat = "pointinterval" to produce point estimates and credible intervals.

A full list of options and examples is found in the ggdist vignette vignette("slabinterval", package = "ggdist").

A ggplot object is returned which can be further modified through the usual ggplot2 functions to add further aesthetics, geoms, themes, etc.

See Also

summary.nma_nodesplit_df()

Examples

# \donttest{
# Run smoking node-splitting example if not already available
if (!exists("smk_fit_RE_nodesplit")) example("example_smk_nodesplit", run.donttest = TRUE)
# }
# \donttest{
# Summarise the node-splitting results
(smk_nodesplit_summary <- summary(smk_fit_RE_nodesplit))

# Plot the node-splitting results
plot(smk_nodesplit_summary)

# Plot the inconsistency factors instead, change the plot stat to half-eye,
# and add a reference line at 0
plot(smk_nodesplit_summary, pars = "omega", stat = "halfeye", ref_line = 0)

# Plot a comparison of the heterogeneity under the node-split models vs.
# the consistency model
plot(smk_nodesplit_summary, pars = "tau")
# }