| plot.nma_summary {multinma} | R Documentation |
Plots of summary results
Description
The plot method for nma_summary objects is used to produce plots of
parameter estimates (when called on a stan_nma object or its summary),
relative effects (when called on the output of relative_effects()),
absolute predictions (when called on the output of predict.stan_nma()),
posterior ranks and rank probabilities (when called on the output of
posterior_ranks() or posterior_rank_probs()).
Usage
## S3 method for class 'nma_summary'
plot(
x,
...,
stat = "pointinterval",
orientation = c("horizontal", "vertical", "y", "x"),
ref_line = NA_real_
)
## S3 method for class 'nma_parameter_summary'
plot(
x,
...,
stat = "pointinterval",
orientation = c("horizontal", "vertical", "y", "x"),
ref_line = NA_real_
)
## S3 method for class 'nma_rank_probs'
plot(x, ...)
## S3 method for class 'surv_nma_summary'
plot(x, ..., stat = "lineribbon")
Arguments
x |
A |
... |
Additional arguments passed on to the underlying |
stat |
Character string specifying the |
orientation |
Whether the |
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 uses
ggdist::stat_pointinterval(), to
produce medians and 95% Credible Intervals with 66% inner bands. Additional
arguments in ... are passed to the ggdist stat, to customise the
output. For example, to produce means and Credible Intervals, specify
point_interval = "mean_qi". To produce an 80% Credible Interval with no
inner band, specify .width = c(0, 0.8).
Alternative stats can be specified to produce different summaries. For
example, specify stat = "[half]eye" to produce (half) eye plots, or stat = "histinterval" to produce histograms with intervals.
A full list of options and examples is found in the ggdist vignette
vignette("slabinterval", package = "ggdist").
For survival/hazard/cumulative hazard curves estimated from survival
models, the default uses
ggdist::stat_lineribbon() which
produces curves of posterior medians with 50%, 80%, and 95% Credible
Interval bands. Again, additional arguments in ... are passed to the
ggdist stat. For example, to produce posterior means and 95% Credible
bands, specify point_interval = "mean_qi" and .width = 0.95.
A ggplot object is returned which can be further modified through the
usual ggplot2 functions to add further aesthetics, geoms, themes, etc.
Value
A ggplot object.
Examples
## Smoking cessation
# Run smoking RE NMA example if not already available
if (!exists("smk_fit_RE")) example("example_smk_re", run.donttest = TRUE)
# Produce relative effects
smk_releff_RE <- relative_effects(smk_fit_RE)
plot(smk_releff_RE, ref_line = 0)
# Customise plot options
plot(smk_releff_RE, ref_line = 0, stat = "halfeye")
# Further customisation is possible with ggplot commands
plot(smk_releff_RE, ref_line = 0, stat = "halfeye", slab_alpha = 0.6) +
ggplot2::aes(slab_fill = ggplot2::after_stat(ifelse(x < 0, "darkred", "grey60")))
# Produce posterior ranks
smk_rank_RE <- posterior_ranks(smk_fit_RE, lower_better = FALSE)
plot(smk_rank_RE)
# Produce rank probabilities
smk_rankprob_RE <- posterior_rank_probs(smk_fit_RE, lower_better = FALSE)
plot(smk_rankprob_RE)
# Produce cumulative rank probabilities
smk_cumrankprob_RE <- posterior_rank_probs(smk_fit_RE, lower_better = FALSE,
cumulative = TRUE)
plot(smk_cumrankprob_RE)
# Further customisation is possible with ggplot commands
plot(smk_cumrankprob_RE) +
ggplot2::facet_null() +
ggplot2::aes(colour = Treatment)