BCEA (version 2.2-2)

eib.plot: Expected Incremental Benefit (EIB) plot

Description

Produces a plot of the Expected Incremental Benefit (EIB) as a function of the willingness to pay

Usage

eib.plot(he, comparison=NULL, pos=c(1,0), size=NULL, 
         plot.cri = NULL, graph=c("base","ggplot2"), ...)

Arguments

he

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

comparison

Selects the comparator, in case of more than two interventions being analysed. Default as NULL plots all the comparisons together. Any subset of the possible comparisons can be selected (e.g., comparison=c(1,3) or compari

pos

Parameter to set the position of the legend; for a single comparison plot, the ICER legend position. Can be given in form of a string (bottom|top)(right|left) for base graphics and bottom|top|left|right for ggplot2. It can be a

size

Value (in millimetres) of the size of the willingness to pay label. Used only if graph="ggplot2", otherwise it will be ignored with a message. If set to NA, the break-even point line(s) and label(s) are suppressed, with both ba

plot.cri

Logical value. Should the credible intervals be plotted along with the expected incremental benefit? Default as NULL draws the 95% credible intervals if only one comparison is selected, and does not include them for multiple comparisons. S

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".

...

If graph="ggplot2" and a named theme object is supplied, it will be added to the ggplot object. If plot.cri=TRUE the level of the interval can be set using the argument alpha, with default at alpha=0.05

Value

• eib
  A ggplot object containing the requested plot. Returned only if graph="ggplot2".
• The function produces a plot of the Expected Incremental Benefit as a function of the discrete grid approximation of the willingness to pay parameter. The break even point (i.e. the point in which the EIB=0, ie when the optimal decision changes from one intervention to another) is also showed by default. The value k* is the discrete grid approximation of the ICER.

References

Baio, G., Dawid, A. P. (2011). Probabilistic Sensitivity Analysis in Health Economics. Statistical Methods in Medical Research doi:10.1177/0962280211419832.

Baio G. (2012). Bayesian Methods in Health Economics. CRC/Chapman Hall, London

See Also

bcea, ib.plot, ceplane.plot