#' Plot the second stage sample sizes of two-stage adaptive single-arm trial
#' designs for a single binary endpoint
#'
#' Plots the second stage sample sizes of two-stage adaptive single-arm trial
#' designs determined using \code{des_adaptive()}. The values of
#' \ifelse{html}{\out{<i>n</i><sub>2</sub>(<i>s</i><sub>n<sub>1</sub>
#' </sub>))}}{\eqn{n_2(\tilde{s}_1)}} are plotted.
#'
#' Support is available to simultaneously plot the second stage sample sizes of multiple
#' two-stage adaptive single-arm clinical trial designs for a single binary primary
#' endpoint.
#'
#' @param x An object of class \code{"sa_des_adaptive"}, as returned by \code{des_adaptive()}.
#' @param ... Additional objects of class \code{"sa_des_adaptive"}. These will be grouped
#' in to a list named \code{"add_des"}.
#' @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{$plot_des} containing the available plots.
#' \item Each of the input variables as specified, subject to internal modification.
#' }
#' @examples
#' # Find the optimal adaptive two-stage design for the default parameters
#' des <- des_adaptive()
#' # Plot the stopping boundaries
#' plot(des)
#' # Find the optimal adaptive two-stage design for a 10% type-I error rate
#' des_10 <- des_adaptive(alpha = 0.1)
#' # Plot the second stage sample sizes for both designs
#' plot(des, des_10)
#' @seealso \code{\link{des_adaptive}}, \code{\link{opchar_adaptive}}, and their
#' associated \code{plot} family of functions.
#' @export
plot.sa_des_adaptive <- function(x, ..., output = F) {
des <- x
##### Input Checking #########################################################
check_sa_des_adaptive(des, "des")
add_des <- pryr::named_dots(...)
num_add_des <- length(add_des)
if (num_add_des > 0) {
for (i in 1:num_add_des) {
check_sa_des_adaptive(eval(add_des[[i]]), paste("add_des", i, sep = ""))
}
for (i in 1:num_add_des) {
if (eval(add_des[[i]])$des$pi0 != des$des$pi0) {
stop("Each supplied design must have been designed for the same value of pi0")
}
}
}
check_logical(output, "output")
##### Main Computations ######################################################
plot_des <- list()
if (num_add_des == 0) {
add_des <- NULL
int_tibble <- tibble::tibble(s1 = 0:des$des$n1,
n2 = des$des$n2)
plot_des$`n2(tilde(s)1)` <- ggplot2::ggplot(int_tibble,
ggplot2::aes(x = s1, y = n2)) +
ggplot2::geom_point() +
ggplot2::geom_line() +
ggplot2::xlab(expression(italic(tilde(s)[1]))) +
ggplot2::ylab(expression(paste(italic(n[2]), "(", italic(tilde(s)[1]), ")",
sep = ""))) +
theme_singlearm() +
ggplot2::scale_x_continuous(minor_breaks = NULL) +
ggplot2::scale_y_continuous(minor_breaks = NULL)
print(plot_des$`n2(tilde(s)1)`)
} else {
all_des <- list()
all_des[[1]] <- des
for (i in 1:num_add_des) {
all_des[[i + 1]] <- eval(add_des[[i]])
}
num_des <- 1 + num_add_des
int_tibble <- NULL
for (i in 1:num_des) {
int_tibble <- rbind(int_tibble, cbind(paste("Design", i),
0:all_des[[i]]$des$n1,
all_des[[i]]$des$n2))
}
int_tibble <- tibble::tibble(Design = factor(int_tibble[, 1],
levels = unique(int_tibble[, 1])),
s1 = as.integer(int_tibble[, 2]),
n2 = as.integer(int_tibble[, 3]))
plot_des$`n2(tilde(s)1)` <- ggplot2::ggplot(int_tibble,
ggplot2::aes(x = s1, y = n2,
colour = Design)) +
ggplot2::geom_point() +
ggplot2::geom_line() +
ggplot2::xlab(expression(italic(tilde(s)[1]))) +
ggplot2::ylab(expression(paste(italic(n[2]), "(", italic(tilde(s)[1]), ")",
sep = ""))) +
theme_singlearm() +
ggplot2::scale_x_continuous(minor_breaks = NULL) +
ggplot2::scale_y_continuous(minor_breaks = NULL)
print(plot_des$`n2(tilde(s)1)`)
}
##### Outputting #############################################################
if (output) {
return(list(plot_des = plot_des, des = des, add_des = add_des))
}
}
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