pvEBayes (version 0.2.1)

eyeplot_pvEBayes: Generate an eyeplot showing the distribution of posterior draws for selected drugs and adverse events

Description

This function creates an eyeplot to visualize the posterior distributions of \(\lambda_{ij}\) for selected AEs and drugs. The plot displays posterior median, 90 percent credible interval for each selected AE-drug combination.

Usage

eyeplot_pvEBayes(
  x,
  num_top_AEs = 10,
  num_top_drugs = 8,
  specified_AEs = NULL,
  specified_drugs = NULL,
  N_threshold = 1,
  text_shift = 4,
  x_lim_scalar = 1.3,
  text_size = 3,
  log_scale = FALSE
)

Value

a ggplot2 object.

Arguments

x

a pvEBayes object, which is the output of the function pvEBayes or pvEBayes_tune.

num_top_AEs

a number of most significant AEs appearing in the plot. Default to 10.

num_top_drugs

a number of most significant drugs appearing in the plot. Default to 7.

specified_AEs

a vector of AE names that are specified to appear in the plot. If a vector of AEs is given, argument num_top_AEs will be ignored.

specified_drugs

a vector of drug names that are specified to appear in the plot. If a vector of drugs is given, argument num_top_drugs will be ignored.

N_threshold

a integer greater than 0. Any AE-drug combination with observation smaller than N_threshold will be filtered out.

text_shift

numeric. Controls the relative position of text labels, (e.g., "N = 1", "E = 2"). A larger value shifts the "E = 2" further away from its original position.

x_lim_scalar

numeric. An x-axis range scalar that ensures text labels are appropriately included in the plot.

text_size

numeric. Controls the size of text labels, (e.g., "N = 1", "E = 2").

log_scale

logical. If TRUE, the eye plot displays the posterior distribution of \(\log(\lambda_{ij})\) for the selected AEs and drugs.

Examples

fit <- pvEBayes(
  contin_table = statin2025_44, model = "general-gamma",
  alpha = 0.3, n_posterior_draws = 1000
)

AE_names <- rownames(statin2025_44)[1:6]
drug_names <- colnames(statin2025_44)[-7]

eyeplot_pvEBayes(
  x = fit
)