#' Plot the p-values, and the p-value calculation procedures performance, in a group sequential
#' single-arm trial design for a single binary endpoint
#'
#' Plots the p-values, and the performance of the p-value calculation procedures,
#' in a group sequential single-arm trial design for a single binary endpoint
#' determined using \code{pval_gs()}. A range of plots are available, of which
#' the p-values and the expected p-value curve will be printed by default.
#'
#' @param x An object of class \code{"sa_pval_gs"}, as returned by \code{pval_gs()}.
#' @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{$plot_des} containing the available plots.
#' \item Each of the input variables as specified, subject to internal modification.
#' }
#' @examples
#' # Find the optimal group sequential design for the default parameters
#' des <- des_gs()
#' # Determine the performance of the p-value calculation procedures for a range of
#' # possible response probabilities
#' pval <- pval_gs(des, pi = seq(from = 0, to = 1, by = 0.01))
#' # Plot the p-values and the calculation procedures performance
#' plot(pval)
#' @seealso \code{\link{des_gs}}, \code{\link{opchar_gs}}, \code{\link{est_gs}}, \code{\link{pval_gs}},
#' and \code{\link{ci_gs}}, and their associated \code{plot} family of functions.
#' @export
plot.sa_pval_gs <- function(x, ..., output = F) {
pval <- x
##### Input Checking #########################################################
check_sa_pval_gs(pval)
check_logical(output, "output")
##### Main Computations ######################################################
plot_pval <- list()
new_levels <- levels(pval$pval$method)
for (i in 1:length(new_levels)) {
if (new_levels[i] == "conditional") {
new_levels[i] <- "Conditional"
} else if (new_levels[i] == "mle") {
new_levels[i] <- "MLE-ordering"
} else if (new_levels[i] == "naive") {
new_levels[i] <- "Naive"
} else {
new_levels[i] <- "UMVUE-ordering"
}
}
pval$pval$method <- plyr::mapvalues(pval$pval$method,
from = levels(pval$pval$method),
to = new_levels)
pval$pval$k <- plyr::mapvalues(pval$pval$k, from = levels(pval$pval$k),
to = paste("k =", levels(pval$pval$k)))
plot_pval$pval <- ggplot2::ggplot(data = pval$pval,
ggplot2::aes(x = s, y = `p(s,m)`,
color = method)) +
ggplot2::xlab(expression(italic(s))) +
ggplot2::ylab(expression(paste(italic(p), "(", italic(s),
",", italic(n), "|", pi[0],
")", sep = ""))) +
ggplot2::geom_hline(yintercept = pval$des$alpha,
linetype = 2) +
ggplot2::geom_point() +
ggplot2::geom_line() + ggplot2::facet_grid(.~k) +
ggthemes::scale_color_ptol("method") +
theme_singlearm()
print(plot_pval$pval)
if (!is.null(pval$perf)) {
new_levels <- levels(pval$perf$method)
for (i in 1:length(new_levels)) {
if (new_levels[i] == "conditional") {
new_levels[i] <- "Conditional"
} else if (new_levels[i] == "mle") {
new_levels[i] <- "MLE-ordering"
} else if (new_levels[i] == "naive") {
new_levels[i] <- "Naive"
} else {
new_levels[i] <- "UMVUE-ordering"
}
}
pval$perf$method <- plyr::mapvalues(pval$perf$method,
from = levels(pval$perf$method),
to = new_levels)
if (min(pval$pi) < pval$des$des$pi0) {
red <- tibble::tibble(start = min(pval$pi),
end = min(pval$des$des$pi0, max(pval$pi)))
}
if (all(min(pval$pi) <= pval$des$des$pi1,
max(pval$pi) >= pval$des$des$pi0)) {
amber <- tibble::tibble(start = max(pval$des$des$pi0, min(pval$pi)),
end = min(pval$des$des$pi1, max(pval$pi)))
}
if (max(pval$pi) > pval$des$des$pi1) {
green <- tibble::tibble(start = max(pval$des$des$pi1,
min(pval$pi)), end = max(pval$pi))
}
plot_pval$`E(p|pi)` <- ggplot2::ggplot()
if (min(pval$pi) < pval$des$des$pi0) {
plot_pval$`E(p|pi)` <- plot_pval$`E(p|pi)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(pval$pi) <= pval$des$des$pi1,
max(pval$pi) >= pval$des$des$pi0)) {
plot_pval$`E(p|pi)` <- plot_pval$`E(p|pi)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(pval$pi) > pval$des$des$pi1) {
plot_pval$`E(p|pi)` <- plot_pval$`E(p|pi)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plot_pval$`E(p|pi)` <- plot_pval$`E(p|pi)` +
ggplot2::geom_hline(yintercept = pval$des$alpha,
linetype = 2) +
ggplot2::geom_line(data = pval$perf,
ggplot2::aes(x = pi,
y = `E(p|pi)`,
color = method)) +
ggplot2::xlab(expression(pi)) +
ggplot2::ylab(expression(paste("E(", italic(p),
"|", pi, ")",
sep = ""))) +
ggthemes::scale_color_ptol("method") +
ggplot2::theme(legend.title =
ggplot2::element_blank(),
legend.position = "bottom") +
theme_singlearm() +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(pval$perf$pi),
max(pval$perf$pi)))
print(plot_pval$`E(p|pi)`)
plot_pval$`Var(p|pi)` <- ggplot2::ggplot()
if (min(pval$pi) < pval$des$des$pi0) {
plot_pval$`Var(p|pi)` <- plot_pval$`Var(p|pi)` +
ggplot2::geom_rect(data = red,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "firebrick2")
}
if (all(min(pval$pi) <= pval$des$des$pi1,
max(pval$pi) >= pval$des$des$pi0)) {
plot_pval$`Var(p|pi)` <- plot_pval$`Var(p|pi)` +
ggplot2::geom_rect(data = amber,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "orange")
}
if (max(pval$pi) > pval$des$des$pi1) {
plot_pval$`Var(p|pi)` <- plot_pval$`Var(p|pi)` +
ggplot2::geom_rect(data = green,
ggplot2::aes(xmin = start,
xmax = end,
ymin = -Inf,
ymax = Inf),
alpha = 0.1,
fill = "green4")
}
plot_pval$`Var(p|pi)` <- plot_pval$`Var(p|pi)` +
ggplot2::geom_line(data = pval$perf,
ggplot2::aes(x = pi,
y = `Var(p|pi)`,
color = method)) +
ggplot2::xlab(expression(pi)) +
ggplot2::ylab(expression(paste(italic(Var), "(",
italic(p), "|",
pi, ")",
sep = ""))) +
ggthemes::scale_color_ptol("method") +
ggplot2::theme(legend.title =
ggplot2::element_blank(),
legend.position = "bottom") +
theme_singlearm() +
ggplot2::scale_x_continuous(expand = c(0, 0),
limits = c(min(pval$perf$pi),
max(pval$perf$pi)))
}
##### Outputting #############################################################
if (output) {
output <- list(plot_pval = plot_pval, pval = pval)
return(output)
}
}
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