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#' @include randPar.R
#' @include pbrPar.R
NULL
###############################################
# --------------------------------------------#
# Class rarPar #
# --------------------------------------------#
###############################################
# --------------------------------------------
# Function for validity check
# --------------------------------------------
# Validity check function for objects of the rarPar class
#
# @inheritParams overview
#
# @return Returns a \code{TRUE}, if the settings of the object are valid.
validaterarPar <- function(object) {
errors <- character()
N <- object@N
ratio <- object@ratio
if (!(N %% sum(ratio) == 0)) {
msg <- paste("N = ", N, " is not a multiple of sum(ratio) = "
, sum(ratio),".", sep = "")
errors <- c(errors, msg)
}
if (length(errors) == 0) TRUE else errors
}
# --------------------------------------------
# Class definition for rarPar
# --------------------------------------------
# Randomization parameters generic
setClass("rarPar", contains = "randPar", validity = validaterarPar)
# --------------------------------------------
# Constructor function for rarPar
# --------------------------------------------
#' Representing Random Allocation Rule
#'
#' Represents the randomization procedure Random Allocation Rule.
#'
#' @details
#' Fix a total sample size \code{N} the number of treatment groups \code{K},
#' and the vector of the \code{ratio}. Afterwards, all patients are assigned
#' according to the ratio to the corresponding treatment groups.
#' All randomization sequences are equiprobable.
#'
#' @family randomization procedures
#'
#' @inheritParams overview
#'
#' @return
#' \code{S4} object of the class \code{rarPar}.
#'
#' @export
#'
#' @references
#' W. F. Rosenberger and J. M. Lachin (2002) \emph{Randomization in Clinical Trials}.
#' Wiley.
rarPar <- function(N, K = 2, ratio = rep(1, K), groups = LETTERS[1:K]) {
new("rarPar", N = N, K = K, ratio = ratio, groups = groups)
}
# --------------------------------------------
# Methods for rarPar
# --------------------------------------------
#' @rdname generateAllSequences
setMethod("getAllSeq",
signature(obj = "rarPar"),
function(obj) {
if(obj@K != 2 || !identical(obj@ratio, c(1,1))) {
stop("Only possible for K equals 2 and ratio corresponds to c(1,1).")
}
allSeqs <- compltSet(obj)
finBal <- apply(allSeqs, 1, function(x) 2*sum(x) == length(x))
new("rarSeq",
M = allSeqs[finBal, ] ,
N = N(obj),
K = K(obj),
ratio = obj@ratio,
groups = obj@groups)
}
)
#' @rdname generateRandomSequences
setMethod("genSeq",
signature(obj = "rarPar", r = "numeric", seed = "numeric"),
function(obj, r, seed) {
set.seed(seed)
new("rRarSeq",
M = t(sapply(1:r, function(x) {
blockRand(bc = N(obj), K = K(obj), ratio = ratio(obj))
})),
N = N(obj),
K = K(obj),
ratio = obj@ratio,
groups = obj@groups,
seed = seed)
}
)
#' @rdname generateRandomSequences
setMethod("genSeq",
signature(obj = "rarPar", r = "missing", seed = "numeric"),
function(obj, r, seed) {
set.seed(seed)
new("rRarSeq",
M = t(blockRand(bc = N(obj), K = K(obj), ratio = ratio(obj))),
N = N(obj),
K = K(obj),
ratio = obj@ratio,
groups = obj@groups,
seed = seed)
}
)
#' @rdname generateRandomSequences
setMethod("genSeq", signature(obj = "rarPar", r = "numeric", seed = "missing"),
function(obj, r, seed) {
seed = sample(1:(10^6),1)
set.seed(seed)
new("rRarSeq",
M = t(sapply(1:r, function(x) {
blockRand(bc = N(obj), K = K(obj), ratio = ratio(obj))
})),
N = N(obj),
K = K(obj),
ratio = obj@ratio,
groups = obj@groups,
seed = seed)
}
)
#' @rdname generateRandomSequences
setMethod("genSeq", signature(obj = "rarPar", r = "missing", seed = "missing"),
function(obj, r, seed) {
seed = sample(1:(10^6),1)
set.seed(seed)
new("rRarSeq",
M = t(blockRand(bc = N(obj), K = K(obj), ratio = ratio(obj))),
N = N(obj),
K = K(obj),
ratio = obj@ratio,
groups = obj@groups,
seed = seed)
}
)
#' @rdname getDesign
setMethod("getDesign",
signature(obj = "rarPar"),
function(obj) {
"RAR"
}
)
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