ceac | R Documentation |
ceac
is used to compute and plot the cost-effectiveness acceptability
curves (CEAC) from a probabilistic sensitivity analysis (PSA) dataset.
ceac(wtp, psa)
wtp |
numeric vector with willingness-to-pay (WTP) thresholds |
psa |
psa object from |
ceac
computes the probability of each of the strategies being
cost-effective at each wtp
threshold. The returned object has classes
ceac
and data.frame
, and has its own plot method (plot.ceac
).
An object of class ceac
that can be visualized with plot
. The ceac
object is a data.frame that shows the proportion of PSA samples for which each strategy at each
WTP threshold is cost-effective. The final column indicates whether or not the strategy at a
particular WTP is on the cost-efficient frontier.
plot.ceac
, summary.ceac
# psa input provided with package
data("example_psa")
example_psa_obj <- make_psa_obj(example_psa$cost, example_psa$effectiveness,
example_psa$parameters, example_psa$strategies)
# define wtp threshold vector (can also use a single wtp)
wtp <- seq(1e4, 1e5, by = 1e4)
ceac_obj <- ceac(wtp, example_psa_obj)
plot(ceac_obj) # see ?plot.ceac for options
# this is most useful when there are many strategies
# warnings are printed to describe strategies that
# have been filtered out
plot(ceac_obj, min_prob = 0.5)
# standard ggplot layers can be used
plot(ceac_obj) +
labs(title = "CEAC", y = "Pr(Cost-effective) at WTP")
# the ceac object is also a data frame
head(ceac_obj)
# summary() tells us the regions of cost-effectiveness for each strategy.
# Note that the range_max column is an open parenthesis, meaning that the
# interval over which that strategy is cost-effective goes up to but does not include
# the value in the range_max column.
summary(ceac_obj)
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