#' Plot the point estimates, and the point estimation procedures performance, in
#' a curtailed group sequential single-arm trial design for a single binary
#' endpoint
#'
#' Plots the point estimates, and the performance of the point estimation
#' procedure, in a curtailed group sequential single-arm trial design for a
#' single binary endpoint determined using \code{est_curtailed()}. A range of
#' plots are available, of which the bias curve will be printed by default.
#'
#' @param x An object of class \code{"sa_est_curtailed"}, as returned by
#' \code{est_curtailed()}.
#' @param ... Included for compatibility with the generic. Not currently used.
#' @param output A logical variable indicating whether the outputs described
#' below should be returned.
#' @return If \code{output = TRUE}, a list containing the following elements is
#' returned
#' \itemize{
#' \item A list in the slot \code{$plot_des} containing the available plots.
#' \item Each of the input variables as specified, subject to internal
#' modification.
#' }
#' @examples
#' # Find the optimal curtailed group sequential design for the default
#' parameters
#' des <- des_curtailed()
#' # Determine the performance of the point estimation procedure for a range of
#' # possible response probabilities
#' est <- est_curtailed(des, pi = seq(0, 1, 0.01))
#' # Plot the point estimates and the estimation procedure performance
#' plot(est)
#' @seealso \code{\link{des_curtailed}}, \code{\link{opchar_curtailed}},
#' \code{\link{est_curtailed}}, \code{\link{pval_curtailed}},
#' \code{\link{ci_curtailed}}, and their associated \code{plot} family of
#' functions.
#' @export
plot.sa_est_curtailed <- function(x, ..., output = F) {
est <- x
##### Input Checking #########################################################
check_sa_est_curtailed(est)
check_logical(output, "output")
##### Main Computations ######################################################
plot_est <- list()
if (!is.null(est$perf)) {
new_levels <- levels(est$perf$method)
for (i in 1:length(new_levels)) {
if (new_levels[i] == "bias_adj") {
new_levels[i] <- "Bias adjusted"
} else if (new_levels[i] == "bias_sub") {
new_levels[i] <- "Bias subtracted"
} else if (new_levels[i] == "conditional") {
new_levels[i] <- "Conditional"
} else if (new_levels[i] == "naive") {
new_levels[i] <- "Naive"
} else if (new_levels[i] == "mue") {
new_levels[i] <- "MUE"
} else {
new_levels[i] <- "UMVUE"
}
}
est$perf$method <- plyr::mapvalues(est$perf$method,
from = levels(est$perf$method),
to = new_levels)
if (min(est$pi) < est$des$des$pi0) {
red <- tibble::tibble(start = min(est$pi),
end = min(est$des$des$pi0, max(est$pi)))
}
if (all(min(est$pi) <= est$des$des$pi1,
max(est$pi) >= est$des$des$pi0)) {
amber <- tibble::tibble(start = max(est$des$des$pi0, min(est$pi)),
end = min(est$des$des$pi1, max(est$pi)))
}
if (max(est$pi) > est$des$des$pi1) {
green <- tibble::tibble(start = max(est$des$des$pi1,
min(est$pi)), end = max(est$pi))
}
plot_est$`E(hat(pi)|pi)` <- ggplot2::ggplot()
if (min(est$pi) < est$des$des$pi0) {
plot_est$`E(hat(pi)|pi)` <- plot_est$`E(hat(pi)|pi)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(est$pi) <= est$des$des$pi1,
max(est$pi) >= est$des$des$pi0)) {
plot_est$`E(hat(pi)|pi)` <- plot_est$`E(hat(pi)|pi)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(est$pi) > est$des$des$pi1) {
plot_est$`E(hat(pi)|pi)` <- plot_est$`E(hat(pi)|pi)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plot_est$`E(hat(pi)|pi)` <- plot_est$`E(hat(pi)|pi)` +
ggplot2::geom_abline(slope = 1,
intercept = 0,
linetype = 2) +
ggplot2::geom_hline(yintercept = est$des$pi0,
linetype = 2) +
ggplot2::geom_hline(yintercept = est$des$pi1,
linetype = 2) +
ggplot2::geom_line(data = est$perf,
ggplot2::aes(x = pi,
y = `E(hat(pi)|pi)`, colour = method)) +
ggplot2::xlab(expression(pi)) +
ggplot2::ylab(expression(paste("E(", hat(pi),
"|", pi, ")",
sep = ""))) +
theme_singlearm() +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(est$perf$pi),
max(est$perf$pi)))
plot_est$`Var(hat(pi)|pi)` <- ggplot2::ggplot()
if (min(est$pi) < est$des$des$pi0) {
plot_est$`Var(hat(pi)|pi)` <- plot_est$`Var(hat(pi)|pi)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(est$pi) <= est$des$des$pi1,
max(est$pi) >= est$des$des$pi0)) {
plot_est$`Var(hat(pi)|pi)` <- plot_est$`Var(hat(pi)|pi)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(est$pi) > est$des$des$pi1) {
plot_est$`Var(hat(pi)|pi)` <- plot_est$`Var(hat(pi)|pi)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plot_est$`Var(hat(pi)|pi)` <- plot_est$`Var(hat(pi)|pi)` +
ggplot2::geom_line(data = est$perf,
ggplot2::aes(x = pi,
y = `Var(hat(pi)|pi)`, colour = method)) +
ggplot2::xlab(expression(pi)) +
ggplot2::ylab(expression(paste(italic(Var), "(",
hat(pi), "|",
pi, ")",
sep = ""))) +
theme_singlearm() +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(est$perf$pi),
max(est$perf$pi)))
plot_est$`Bias(hat(pi)|pi)` <- ggplot2::ggplot()
if (min(est$pi) < est$des$des$pi0) {
plot_est$`Bias(hat(pi)|pi)` <- plot_est$`Bias(hat(pi)|pi)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(est$pi) <= est$des$des$pi1,
max(est$pi) >= est$des$des$pi0)) {
plot_est$`Bias(hat(pi)|pi)` <- plot_est$`Bias(hat(pi)|pi)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(est$pi) > est$des$des$pi1) {
plot_est$`Bias(hat(pi)|pi)` <- plot_est$`Bias(hat(pi)|pi)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plot_est$`Bias(hat(pi)|pi)` <- plot_est$`Bias(hat(pi)|pi)` +
ggplot2::geom_hline(yintercept = 0,
linetype = 2) +
ggplot2::geom_line(data = est$perf,
ggplot2::aes(x = pi,
y = `Bias(hat(pi)|pi)`, colour = method)) +
ggplot2::xlab(expression(pi)) +
ggplot2::ylab(expression(paste(italic(Bias), "(",
hat(pi),
"|", pi,
")",
sep = ""))) +
theme_singlearm() +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(est$perf$pi),
max(est$perf$pi)))
print(plot_est$`Bias(hat(pi)|pi)`)
plot_est$`RMSE(hat(pi)|pi)` <- ggplot2::ggplot()
if (min(est$pi) < est$des$des$pi0) {
plot_est$`RMSE(hat(pi)|pi)` <- plot_est$`RMSE(hat(pi)|pi)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(est$pi) <= est$des$des$pi1,
max(est$pi) >= est$des$des$pi0)) {
plot_est$`RMSE(hat(pi)|pi)` <- plot_est$`RMSE(hat(pi)|pi)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(est$pi) > est$des$des$pi1) {
plot_est$`RMSE(hat(pi)|pi)` <- plot_est$`RMSE(hat(pi)|pi)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plot_est$`RMSE(hat(pi)|pi)` <- plot_est$`RMSE(hat(pi)|pi)` +
ggplot2::geom_line(data = est$perf,
ggplot2::aes(x = pi,
y = `RMSE(hat(pi)|pi)`, colour = method)) +
ggplot2::xlab(expression(pi)) +
ggplot2::ylab(expression(paste(italic(RMSE), "(",
hat(pi),
"|", pi,
")",
sep = ""))) +
theme_singlearm() +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(est$perf$pi),
max(est$perf$pi)))
}
##### Outputting #############################################################
if (output) {
output <- list(plot_est = plot_est, est = est)
return(output)
}
}
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