plot_prior_posterior: Plot prior vs posterior distribution

In multinma: Bayesian Network Meta-Analysis of Individual and Aggregate Data

Plot prior vs posterior distribution

Description

Produce plots comparing the prior and posterior distributions of model parameters.

Usage

plot_prior_posterior(
  x,
  ...,
  prior = NULL,
  post_args = list(),
  prior_args = list(),
  overlay = c("prior", "posterior"),
  ref_line = NA_real_
)

Arguments

x	A stan_nma object
...	Additional arguments passed on to methods
prior	Character vector selecting the prior and posterior distribution(s) to plot. May include "intercept", "trt", "het", "reg", or "aux", as appropriate.
post_args	List of arguments passed on to ggplot2::geom_histogram to control plot output for the posterior distribution
prior_args	List of arguments passed on to ggplot2::geom_path to control plot output for the prior distribution. Additionally, n controls the number of points the density curve is evaluated at (default 500), and p_limits controls the endpoints of the curve as quantiles (default c(.001, .999)).
overlay	String, should prior or posterior be shown on top? Default "prior".
ref_line	Numeric vector of positions for reference lines, by default no reference lines are drawn

Details

Prior distributions are displayed as lines, posterior distributions are displayed as histograms.

Value

A ggplot object.

Examples

## Smoking cessation NMA

# Run smoking RE NMA example if not already available
if (!exists("smk_fit_RE")) example("example_smk_re", run.donttest = TRUE)


# Plot prior vs. posterior, by default all parameters are plotted
plot_prior_posterior(smk_fit_RE)

# Plot prior vs. posterior for heterogeneity SD only
plot_prior_posterior(smk_fit_RE, prior = "het")

# Customise plot
plot_prior_posterior(smk_fit_RE, prior = "het",
                     prior_args = list(colour = "darkred", size = 2),
                     post_args = list(alpha = 0.6))

multinma documentation built on May 31, 2023, 5:46 p.m.