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#' @rdname ceac.plot
#'
#' @template args-he
#' @template args-comparison
#' @template args-pos
#' @template args-graph
#'
#' @return \item{ceac}{If `graph = "ggplot2"` a ggplot object, or if `graph = "plotly"`
#' a plotly object containing the requested plot. Nothing is returned when `graph = "base"`,
#' the default.} The function produces a plot of the
#' cost-effectiveness acceptability curve against the discrete grid of possible
#' values for the willingness to pay parameter. Values of the CEAC closer to 1
#' indicate that uncertainty in the cost-effectiveness of the reference
#' intervention is very low. Similarly, values of the CEAC closer to 0 indicate
#' that uncertainty in the cost-effectiveness of the comparator is very low.
#'
#' @author Gianluca Baio, Andrea Berardi
#' @seealso [bcea()],
#' [plot.bcea()]
#' @references
#'
#' \insertRef{Baio2011}{BCEA}
#'
#' \insertRef{Baio2013}{BCEA}
#'
#' @keywords hplot
#' @export
#'
#' @import ggplot2
#' @importFrom Rdpack reprompt
#'
#' @examples
#' data("Vaccine")
#' he <- BCEA::bcea(eff, cost)
#' ceac.plot(he)
#'
#' ceac.plot(he, graph = "base")
#' ceac.plot(he, graph = "ggplot2")
#' ceac.plot(he, graph = "plotly")
#'
#' ceac.plot(he, graph = "ggplot2",
#' title = "my title",
#' line = list(color = "green"),
#' theme = ggplot2::theme_dark())
#'
#' ## more interventions
#' he2 <- BCEA::bcea(cbind(eff, eff - 0.0002), cbind(cost, cost + 5))
#' mypalette <- RColorBrewer::brewer.pal(3, "Accent")
#' ceac.plot(he2, graph = "ggplot2",
#' title = "my title",
#' theme = ggplot2::theme_dark(),
#' pos = TRUE,
#' line = list(color = mypalette))
#
#' ceac.plot(he, graph = "base", title = "my title", line = list(color = "green"))
#
#' ceac.plot(he2, graph = "base")
#'
#' ceac.plot(he2, graph = "plotly", pos = "bottom")
#'
ceac.plot.bcea <- function(he,
comparison = NULL,
pos = c(1, 0),
graph = c("base", "ggplot2", "plotly"),
...) {
graph <- match.arg(graph)
he <- setComparisons(he, comparison)
graph_params <- prepare_ceac_params(he, ...)
if (is_baseplot(graph)) {
ceac_plot_base(he,
pos_legend = pos,
graph_params)
} else if (is_ggplot(graph)) {
ceac_plot_ggplot(he,
pos_legend = pos,
graph_params, ...)
} else if (is_plotly(graph)) {
ceac_plot_plotly(he,
pos_legend = pos,
graph_params)
}
}
#' Cost-Effectiveness Acceptability Curve (CEAC) Plot
#'
#' Produces a plot of the Cost-Effectiveness Acceptability Curve (CEAC) against
#' the willingness to pay threshold.
#'
#' The CEAC estimates the probability of cost-effectiveness, with respect to a
#' given willingness to pay threshold. The CEAC is used mainly to evaluate the
#' uncertainty associated with the decision-making process, since it enables the
#' quantification of the preference of the compared interventions, defined in terms
#' of difference in utilities.
#' Formally, the CEAC is defined as:
#'
#' \deqn{\textrm{CEAC} = P(\textrm{IB}(\theta) > 0)}
#'
#' If the net benefit function is used as utility function, the definition can be
#' re-written as
#'
#' \deqn{\textrm{CEAC} = P(k \cdot \Delta_e - \Delta_c > 0)}
#'
#' effectively depending on the willingness to pay value \eqn{k}.
#'
#' @template args-he
#' @param ... If `graph = "ggplot2"` and a named theme object is supplied,
#' it will be passed to the ggplot2 object. The usual ggplot2 syntax is used.
#' Additional arguments:
#' \itemize{
#' \item `line = list(color)`: specifies the line colour(s) - all graph types.
#' \item `line = list(type)`: specifies the line type(s) as `lty` numeric values - all graph types.
#' \item `line = list(size)`: specifies the line width(s) as numeric values - all graph types.
#' \item `currency`: Currency prefix to willingness to pay values - ggplot2 only.
#' \item `area_include`: logical, include area under the CEAC curves - plotly only.
#' \item `area_color`: specifies the AUC colour - plotly only.}
#' @aliases ceac.plot
#' @export
#'
ceac.plot <- function(he, ...) {
UseMethod('ceac.plot', he)
}
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