In BCEA: Bayesian Cost Effectiveness Analysis

Cost-effectiveness plane

The following graph shows the cost-effectiveness plane. This presents the joint distribution of the population average benefit and cost differential, $(\Delta_e,\Delta_c)$ and can be used to assess the uncertainty underlying the decision-making problem.

Each point in the graph represents a 'potential future' in terms of expected incremental economic outcomes. The shaded portion of the plane is the 'sustainability area'. The more points lay in the sustainability area, the more likely that the reference intervention will turn out to be cost-effective, at a given willingness to pay threshold, $k$ (in this case selected at $k=$ r rmd_params$wtp).

n.ints <- m$n_comparators

if (n.ints == 2) {
  graph <- "base"
  pos <- c(1, 1)
} else {
  graph <- "ggplot2"
  pos <- TRUE
}
ceplane.plot(m, graph = graph, pos = pos, wtp = rmd_params$wtp)