evi.plot.bcea {BCEA}  R Documentation 
Plots the Expected Value of Information (EVI) against the willingness to pay.
## S3 method for class 'bcea' evi.plot(he, graph = c("base", "ggplot2", "plotly"), ...) evi.plot(he, ...)
he 
A 
graph 
A string used to select the graphical engine to use for
plotting. Should (partial)match the three options 
... 
Additional graphical arguments:

eib 
If 
The function produces a plot of the Expected Value of Information as a function of the discrete grid approximation of the willingness to pay parameter. The break even point(s) (i.e. the point in which the EIB=0, ie when the optimal decision changes from one intervention to another) is(are) also showed.
Gianluca Baio, Andrea Berardi
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.
data(Vaccine) m < bcea( e=e, c=c, # defines the variables of # effectiveness and cost ref=2, # selects the 2nd row of (e, c) # as containing the reference intervention interventions=treats, # defines the labels to be associated # with each intervention Kmax=50000, # maximum value possible for the willingness # to pay threshold; implies that k is chosen # in a grid from the interval (0, Kmax) plot=FALSE # plots the results ) evi.plot(m) data(Smoking) treats < c("No intervention", "Selfhelp", "Individual counselling", "Group counselling") m < bcea(e, c, ref = 4, interventions = treats, Kmax = 500) evi.plot(m)