contour.bcea {BCEA}  R Documentation 
Contour Plots for the CostEffectiveness Plane
Description
Contour method for objects in the class bcea
.
Produces a scatterplot of the costeffectiveness plane, with a contourplot
of the bivariate density of the differentials of cost (yaxis) and
effectiveness (xaxis).
Usage
## S3 method for class 'bcea'
contour(
he,
pos = c(0, 1),
graph = c("base", "ggplot2"),
comparison = NULL,
...
)
contour(he, ...)
Arguments
he 
A 
pos 
Parameter to set the position of the legend (only relevant for
multiple interventions, ie more than 2 interventions being compared).
Can be given in form
of a string 
graph 
A string used to select the graphical engine to use for
plotting. Should (partial)match the three options 
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.,

... 
Additional graphical arguments. The usual ggplot2 syntax is used regardless of graph type.

Value
ceplane 
A ggplot object containing the plot. Returned only
if 
Plots the costeffectiveness plane with a
scatterplot of all the simulated values from the (posterior) bivariate
distribution of (\Delta_e, \Delta_c
), the differentials of effectiveness and
costs; superimposes a contour of the distribution and prints the estimated
value of the probability of each quadrant (combination of positive/negative
values for both \Delta_e
and \Delta_c
)
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 14770334, 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()
,
contour2()
Examples
data(Vaccine)
# run the health economic evaluation using BCEA
m < bcea(e=eff,
c=cost, # 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=TRUE # plots the results
)
contour(m)
contour(m, graph = "ggplot2")
contour(m, # uses the results of the economic evaluation
# (a "bcea" object)
comparison=1, # if more than 2 interventions, selects the
# pairwise comparison
nlevels=10, # selects the number of levels to be
# plotted (default=4)
levels=NULL, # specifies the actual levels to be plotted
# (default=NULL, so that R will decide)
scale=1, # scales the bandwidths for both x and
# yaxis (default=0.5)
graph="base" # uses base graphics to produce the plot
)
# use the smoking cessation dataset
data(Smoking)
m < bcea(eff, cost, ref = 4, intervention = treats, Kmax = 500, plot = FALSE)
contour(m)
contour(m, graph = "ggplot2")