ceac: Cost-Effectiveness Acceptability Curve (CEAC)

Description

ceac is used to compute and plot the cost-effectiveness acceptability curves (CEAC) from a probabilistic sensitivity analysis (PSA) dataset.

Usage

ceac(wtp, psa)

Arguments

wtp

numeric vector with willingness-to-pay (WTP) thresholds

psa

psa object from make_psa_obj

Value

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.

Details

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).

Examples

Run this code

# NOT RUN {
# 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)

# }