Skip to contents

Generate a heatmap plot visualizing posterior probabilities for selected drugs and adverse events

Source: R/pvEBayes_object_S3_methods.R
heatmap_pvEBayes.Rd

This function generates a heatmap to visualize the posterior probabilities of being a signal for selected AEs and drugs.

Usage

heatmap_pvEBayes(
  x,
  num_top_AEs = 10,
  num_top_drugs = 8,
  specified_AEs = NULL,
  specified_drugs = NULL,
  cutoff_signal = NULL
)

Arguments

x

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

num_top_AEs

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

num_top_drugs

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.

cutoff_signal

numeric. Threshold for signal detection. An AE-drug combination is classified as a detected signal if its 5th posterior percentile exceeds this threshold.

Value

a ggplot2 object.

Examples


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


heatmap_pvEBayes(
  x = fit,
  num_top_AEs = 10,
  num_top_drugs = 8,
  specified_AEs = NULL,
  specified_drugs = NULL,
  cutoff_signal = 1.001
)