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build_gs_pois.R
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build_gs_pois.R
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#' Build a multi-stage group-sequential multi-arm clinical trial for a Poisson
#' distributed primary outcome
#'
#' \code{build_gs_pois()} builds a multi-stage group-sequential multi-arm
#' clinical trial design object assuming the primary outcome variable is
#' Poisson distributed, like those returned by \code{\link{des_gs_pois}}.
#'
#' @param n10 A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>n</i><sub>10</sub>}}{\eqn{n_{10}}}, the sample size
#' required in the control arm in stage one of the trial. Defaults to \code{54}.
#' @param n1 A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>n</i><sub>1</sub>}}{\eqn{n_1}}, the total sample size
#' required in stage one of the trial. Defaults to \code{n10\*(1 + K\*ratio)}.
#' @param e A \code{\link{numeric}} \code{\link{vector}} indicating the chosen
#' value for \ifelse{html}{\out{<b><i>e</i></b>}}{\eqn{\bold{e}}}, the efficacy
#' (upper) stopping boundaries. Defaults to \code{c(2.42, 2.42)}.
#' @param f A \code{\link{numeric}} \code{\link{vector}} indicating the chosen
#' value for \ifelse{html}{\out{<b><i>f</i></b>}}{\eqn{\bold{f}}}, the futility
#' (lower) stopping boundaries. Defaults to \code{c(-2.42, 2.42)}.
#' @param K A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>K</i>}}{\eqn{\bold{K}}}, the (initial) number of
#' experimental treatment arms. Defaults to \code{2}.
#' @param alpha A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>α</i>}}{\eqn{\alpha}}, the significance level
#' (family-wise error-rate). Defaults to \code{0.025}.
#' @param beta A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>β</i>}}{\eqn{\beta}}, used in the definition of
#' the desired power. Defaults to \code{0.1}.
#' @param lambda0 A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>λ</i><sub>0</sub>}}{\eqn{\lambda_0}}, the
#' event rate in the control arm. Defaults to \code{5}.
#' @param delta1 A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>δ</i><sub>1</sub>}}{\eqn{\delta_1}}, the
#' 'interesting' treatment effect. Defaults to \code{1}.
#' @param delta0 A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>δ</i><sub>0</sub>}}{\eqn{\delta_0}}, the
#' 'uninteresting' treatment effect. Defaults to \code{0}.
#' @param ratio A \code{\link{numeric}} indicating the chosen value for
#' \ifelse{html}{\out{<i>r</i>}}{\eqn{r}}, the stage-wise allocation ratio to
#' present experimental arms. Defaults to \code{1}.
#' @param power A \code{\link{character}} string indicating the chosen type of
#' power to design the trial for. Can be \code{"disjunctive"} or
#' \code{"marginal"}. Defaults to \code{"marginal"}.
#' @param stopping A \code{\link{character}} string indicating the chosen type
#' of stopping rule. Can be \code{"separate"} or \code{"simultaneous"}. Defaults
#' to \code{"simultaneous"}.
#' @param type A \code{\link{character}} string indicating the choice for the
#' stage-wise sample size. Can be \code{"variable"} or \code{"fixed"}. Defaults
#' to \code{"variable"}.
#' @param spacing A \code{\link{numeric}} \code{\link{vector}} indicating the
#' chosen spacing of the interim analyses in terms of the proportion of the
#' maximal possible sample size. It must contain strictly increasing values,
#' with final element equal to \code{1}. Defaults to
#' \code{(1:length(e))/length(e)} (i.e., to equally spaced analyses).
#' @param summary A \code{\link{logical}} variable indicating whether a summary
#' of the function's progress should be printed to the console. Defaults to
#' \code{FALSE}.
#' @return A \code{\link{list}}, with additional class
#' \code{"multiarm_des_gs_pois"}, containing the following elements:
#' \itemize{
#' \item A \code{\link{tibble}} in the slot \code{$opchar} summarising the
#' operating characteristics of the identified design.
#' \item A \code{\link{tibble}} in the slot \code{$pmf_N} summarising the
#' probability mass function of the random required sample size under key
#' scenarios.
#' \item A \code{\link{numeric}} in the slot \code{$maxN} specifying
#' \ifelse{html}{\out{max <i>N</i>}}{max \eqn{N}}, the trial's maximum required
#' sample size.
#' \item A \code{\link{numeric}} in the slot \code{$n_factor}, for internal use
#' in other functions.
#' \item Each of the input variables.
#' }
#' @examples
#' # The design for the default parameters
#' des <- build_gs_pois()
#' @seealso \code{\link{des_gs_pois}}, \code{\link{gui}},
#' \code{\link{opchar_gs_pois}}, \code{\link{plot.multiarm_des_gs_pois}},
#' \code{\link{sim_gs_pois}}.
#' @export
build_gs_pois <- function(n10 = 77, n1 = n10*(1 + K*ratio), e = c(2.42, 2.42),
f = c(-2.42, 2.42), K = 2, alpha = 0.025, beta = 0.1,
lambda0 = 5, delta1 = 1, delta0 = 0, ratio = 1,
power = "marginal", stopping = "simultaneous",
type = "variable", spacing = (1:length(e))/length(e),
summary = FALSE) {
##### Check input variables ##################################################
check_real_range_strict(n10, "n10", c(0, Inf), 1)
check_real_range_strict(n1, "n1", c(0, Inf), 1)
#check_ef(e, f, "e", "f")
J <- length(e)
K <- check_integer_range(K, "K", c(1, Inf), 1)
check_real_range_strict(alpha, "alpha", c(0, 1), 1)
check_real_range_strict(beta, "beta", c(0, 1), 1)
check_real_range_strict(lambda0, "lambda0", c(0, Inf), 1)
check_delta0_delta1(delta0, delta1, "delta0", "delta1", lambda0 = lambda0,
name_lambda0 = "lambda0")
check_real_range_strict(ratio, "ratio", c(0, Inf), 1)
check_belong(power, "power", c("conjunctive", "disjunctive", "marginal"), 1)
check_belong(stopping, "stopping", c("simultaneous", "separate"), 1)
check_belong(type, "type", c("fixed", "variable"), 1)
#check_spacing(spacing, "spacing", J)
check_logical(summary, "summary")
##### Print summary ##########################################################
if (summary) {
#summary_build_gs_pois(n10, n1, e, f, K, alpha, beta, lambda0, delta1,
# delta0, ratio, power, spacing, stopping, type)
message("")
}
##### Perform main computations ##############################################
if (summary) {
message(" Building outputs..")
}
integer <- all(c(n1, n10) %% 1 == 0)
if (type == "variable") {
n_factor <- n10
} else {
n_factor <- n1
}
comp <- components_gs_init(alpha, beta, delta0, delta1, NA, NA, NA,
NA, integer, J, K, power, ratio, spacing,
stopping, summary, type,
lambda0 = lambda0, n_factor = n_factor,
f = f, e = e)
tau <- rbind(numeric(K), rep(delta1, K),
matrix(delta0, K, K) + (delta1 - delta0)*diag(K))
comp <- components_gs_update(comp, tau,
lambda = cbind(lambda0, tau + lambda0))
comp <- opchar_gs_internal(comp)
print(comp)
##### Outputting #############################################################
if (summary) {
message("..outputting.")
}
output <- list(alpha = alpha,
beta = beta,
delta0 = delta0,
delta1 = delta1,
e = comp$e,
efix = NA,
eshape = NA,
f = comp$f,
ffix = NA,
fshape = NA,
integer = integer,
J = J,
K = K,
lambda0 = lambda0,
maxN = comp$opchar$maxN[1],
n_factor = comp$n_factor,
n10 = n10,
n1 = n1,
opchar = comp$opchar,
pmf_N = comp$pmf_N,
power = power,
ratio = ratio,
stopping = stopping,
summary = summary,
type = type)
class(output) <- c("multiarm_des_gs_pois", class(output))
output
}