eib.plot.bcea | R Documentation |
Produces a plot of the Expected Incremental Benefit (EIB) as a function of the willingness to pay.
## S3 method for class 'bcea'
eib.plot(
he,
comparison = NULL,
pos = c(1, 0),
size = NULL,
plot.cri = NULL,
graph = c("base", "ggplot2", "plotly"),
...
)
eib.plot(he, ...)
he |
A |
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.,
|
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 |
size |
Value (in millimetres) of the size of the willingness to pay
label. Used only if |
plot.cri |
Logical value. Should the credible intervals be plotted
along with the expected incremental benefit? Default as |
graph |
A string used to select the graphical engine to use for
plotting. Should (partial-)match the three options |
... |
If
|
eib |
If |
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, i.e. 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.
Gianluca Baio, Andrea Berardi
Baio2011BCEA
\insertRefBaio2013BCEA
bcea()
,
ib.plot()
,
ceplane.plot()
data(Vaccine)
# Runs 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=FALSE # plots the results
)
eib.plot(m)
eib.plot(m, graph = "ggplot2") + ggplot2::theme_linedraw()
data(Smoking)
treats <- c("No intervention", "Self-help",
"Individual counselling", "Group counselling")
m <- bcea(eff, cost, ref = 4, interventions = treats, Kmax = 500)
eib.plot(m)
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