R/bssr.gee.1subgroup.r

In spass: Study Planning and Adaptation of Sample Size

#' @title Blinded Sample Size Recalculation for longitudinal data in a One Subgroup Design
#'
#' @description Given re-estimations from an Internal Pilot Study (IPS), \code{bssr.GEE.1subgroup} re-estimates required sample size given the re-estimated nuisance parameters are given. \code{bssr.gee.1subgroup} is a wrapper for \code{n.gee.1subgroup} where the re-estimation of the variances can be highly dependable on the user and should be supplied separately. see "detail" for more information.
#'
#' @param alpha    level (type I error) to which the hypothesis is tested.
#' @param beta     type II error (power=1-beta) to which an alternative should be proven.
#' @param delta    vector of estimated treatment effect in overall and sub population, c(overall population, only subpopulation).
#' @param k        treatment allocation factor between groups: see 'Details'.
#' @param tail     which type of test is used, e.g. which quartile und H0 is calculated.
#' @param estsigma  vector of re-estimated standard deviations, c(full population, subpopulation). See 'Details'.
#' @param tau      ratio between complementary F/S and sub-population S.
#'
#' @details
#' This function provides a simple warped for \code{n.gee.1subgroup} where instead of initial assumptions, reestimated nuisance parameter are used.
#' For more information see \code{n.gee.1subgroup}.
#' Required samplesize to test alternative \code{delta} with specified power 1-\code{beta} when testing the global null hypothesis \eqn{H_0: \beta_3^F=\beta_3^S=0} to level \code{alpha} is estimated. When testing outcomes have variance \code{estsigma}.
#'
#' For sample sizes \eqn{n_C} and \eqn{n_T} of the control and treatment group respectively, the argument \code{k} is the
#' sample size allocation factor, i.e. \eqn{k = n_T/n_C} and \code{tau} represents the ratio of the sub-population.
#'
#' @return \code{bssr.gee.1subgroup} returns a list containing the recalculated sample sizes along with all relevant parameters. Use \code{\link{summary.bssrest}} for a structured overview.
#'
#' @source \code{bssr.gee.1subgroup} uses code contributed by Roland Gerard Gera.
#'
#' @seealso \code{\link{n.gee.1subgroup}} for sample size calculation prior to a trial and \code{estimcov} how the re-estimate nuisance parameters. See \eqn{sim.gee} for a working example for an initial sample size estimation and a re-estimation mid trial.
#'
#' @examples
#' estimate<-bssr.gee.1subgroup(alpha=0.05,beta=0.2,delta=c(0.1,0.1),estsigma=c(0.8,0.4),tau=0.4, k=1)
#' summary(estimate)
#' @export

bssr.gee.1subgroup <- function(alpha, tail="both",beta=NULL, delta, estsigma, tau=0.5, k = 1) {
  if(alpha >=1 || alpha <=0) stop("Wrong Type-I-Error specefied")
  if(beta >=1 || beta <=0) stop("Wrong Type-II-Error specefied")

  result = n.gee.1subgroup(delta=delta,
                           sigma=estsigma,
                           alpha=alpha,
                           tail=tail,
                           beta=beta,
                           tau=tau ,
                           k = k)

  class(result)<-"bssrest"
  return(result)
}