#' @rdname contour2
#' @importFrom stats sd
#' @importFrom graphics par contour
#'
#' @export
#'
contour2.bcea <- function(he,
comparison = NULL,
wtp = 25000,
graph = c("base", "ggplot2"),
pos = c(0, 1),
...) {
graph_type <- match.arg(graph)
he <- setComparisons(he, comparison)
params <- prep_contour_params(he, ...)
if (is_baseplot(graph_type)) {
# encode characters so that the graph can
# be saved as postscript or pdf
ps.options(encoding = "CP1250")
pdf.options(encoding = "CP1250")
plot_params <-
contour_base_params(he, params)
ceplane.plot(he, comparison = NULL, wtp = wtp, pos = pos, graph = "base", ...)
add_contours(he, plot_params)
} else if (is_ggplot(graph_type)) {
plot_params <-
contour_ggplot_params(he, params, ...)
ceplane.plot(he, comparison = NULL, wtp = wtp, pos = pos, graph = "ggplot2", ...) +
do.call(geom_density_2d, plot_params$contour)
}
}
#' Specialised CE-plane Contour Plot
#'
#' Produces a scatterplot of the cost-effectiveness plane, with a contour-plot
#' of the bivariate density of the differentials of cost (y-axis) and
#' effectiveness (x-axis). Also adds the sustainability area (i.e. below the
#' selected value of the willingness-to-pay threshold).
#'
#' @template args-he
#' @param comparison The comparison being plotted. Default to `NULL`
#' If `graph_type="ggplot2"` the default value will choose all the possible
#' comparisons. Any subset of the possible comparisons can be selected (e.g.,
#' `comparison=c(1,3)`).
#' @param wtp The selected value of the willingness-to-pay. Default is
#' `25000`.
#' @template args-graph
#' @template args-pos
#' @param ... Arguments to be passed to [ceplane.plot()]. See the
#' relative manual page for more details.
#'
#' @return \item{contour}{ A ggplot item containing the requested plot.
#' Returned only if `graph_type="ggplot2"`. } Plots the cost-effectiveness
#' plane with a scatterplot of all the simulated values from the (posterior)
#' bivariate distribution of (\eqn{\Delta_e, \Delta_c}), the differentials of
#' effectiveness and costs; superimposes a contour of the distribution and
#' prints the value of the ICER, together with the sustainability area.
#' @author Gianluca Baio, Andrea Berardi
#' @seealso [bcea()],
#' [ceplane.plot()],
#' [contour()]
#'
#' @references
#' \insertRef{Baio2011}{BCEA}
#'
#' \insertRef{Baio2013}{BCEA}
#'
#' @keywords hplot
#' @import ggplot2
#' @importFrom grDevices ps.options pdf.options
#' @importFrom MASS kde2d
#' @importFrom Rdpack reprompt
#'
#' @examples
#' ## create the bcea object m for the smoking cessation example
#' data(Smoking)
#' m <- bcea(eff, cost, ref = 4, interventions = treats, Kmax = 500)
#'
#' ## produce the plot
#' contour2(m,
#' wtp = 200,
#' graph_type = "base")
#'
#' \donttest{
#' ## or use ggplot2 to plot multiple comparisons
#' contour2(m,
#' wtp = 200,
#' ICER_size = 2,
#' graph_type = "ggplot2")
#' }
#'
#' ## vaccination example
#' data(Vaccine)
#' treats = c("Status quo", "Vaccination")
#' m <- bcea(eff, cost, ref = 2, interventions = treats, Kmax = 50000)
#' contour2(m)
#' contour2(m, wtp = 100)
#'
#' @rdname contour2
#' @export
#'
contour2 <- function(he, ...) {
UseMethod('contour2', he)
}
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