ib.plot.bcea {BCEA}

Incremental Benefit (IB) Distribution Plot

Description

Plots the distribution of the Incremental Benefit (IB) for a given value of the willingness to pay threshold.

Usage

## S3 method for class 'bcea'
ib.plot(
  he,
  comparison = NULL,
  wtp = 25000,
  bw = "bcv",
  n = 512,
  xlim = NULL,
  graph = c("base", "ggplot2"),
  ...
)

ib.plot(he, ...)

Arguments

he

A bcea object containing the results of the Bayesian modelling and the economic evaluation.

comparison

In the case of multiple interventions, specifies the one to be used in comparison with the reference. Default value of NULL forces R to consider the first non-reference intervention as the comparator. Controls which comparator is used when more than 2 interventions are present

wtp

The value of the willingness to pay threshold. Default value at 25000.

bw

Identifies the smoothing bandwidth used to construct the kernel estimation of the IB density.

n

The number of equally spaced points at which the density is to be estimated.

xlim

The limits of the plot on the x-axis.

graph

A string used to select the graphical engine to use for plotting. Should (partial-) match the two options "base" or "ggplot2". Default value is "base".

...

Additional arguments

Value

ib

A ggplot object containing the requested plot. Returned only if graph="ggplot2".

The function produces a plot of the distribution of the Incremental Benefit for a given value of the willingness to pay parameter. The dashed area indicates the positive part of the distribution (i.e. when the reference is more cost-effective than the comparator).

Author(s)

Gianluca Baio, Andrea Berardi

References

Baio G, Dawid aP (2011). “Probabilistic sensitivity analysis in health economics.” Stat. Methods Med. Res., 1–20. ISSN 1477-0334, doi:10.1177/0962280211419832, https://pubmed.ncbi.nlm.nih.gov/21930515/.

Baio G (2013). Bayesian Methods in Health Economics. CRC.

See Also

bcea(), ceplane.plot()

Examples

data("Vaccine")
he <- BCEA::bcea(eff, cost)
ib.plot(he)