R/SimulateAllPatientCovariates.R

In kwathen/OCTOPUS: OCTOPUS

##### COPYRIGHT #############################################################################################################
#
# Copyright (C) 2018 JANSSEN RESEARCH & DEVELOPMENT, LLC
# This package is governed by the JRD OCTOPUS License, which is the
# GNU General Public License V3 with additional terms. The precise license terms are located in the files
# LICENSE and GPL.
#
#############################################################################################################################.

#' @name SimulateAllPatientCovariates
#' @title SimulateAllPatientCovariates
#' @description SimulateAllPatientCovariates {This function is used to simulate all patient covariates in the platform.  }
#' @seealso { \href{https://github.com/kwathen/OCTOPUS/blob/master/R/SimulateAllPatientCovariates.R}{View Code on GitHub} }
#' @export
SimulateAllPatientCovariates <- function( cSimCovariates,  cTrialDesign   )
{
    UseMethod( "SimulateAllPatientCovariates", cSimCovariates )
}

#' @name SimulateAllPatientCovariates
#' @title SimulateAllPatientCovariates
#' @description SimulateAllPatientCovariates {This function is used to simulate all patient covariates in the platform.
#' This function is generic in case there is a need to override but
#' is implemented such that it should be suitable for most cases.  Specifically,
#' this function calls SimulatePatientCovariates for each ISA. }
#' @return A list with length equal to the number of ISAs in the trial.   Each element represents the simulated covariates for each ISA.
#' @seealso { \href{https://github.com/kwathen/OCTOPUS/blob/master/R/SimulateAllPatientCovariates.R}{View Code on GitHub} }
#' @export
SimulateAllPatientCovariates.default <- function( cSimCovariates,  cTrialDesign   )
{
    nQtyPats <- cTrialDesign$nMaxQtyPats
    nQtyCovs <- length( cSimCovariates )
    #iCov     <- 1
    #dfCovRet <- data.frame( matrix( NA, nrow = nQtyPats, ncol = nQtyCovs ) )
    #Estimate a new nQtyPats  the likelyhood of a group is low that we we could
    # avoid repeated calls to Simulating additonal patients ect
    nQtyPatsToSimulate <- EstimateNumberOfPatientsToSimulate( cSimCovariates, nQtyPats )
    nQtyISAs           <- cTrialDesign$nQtyISAs

    dfCovRet <- data.frame( mapply(FUN = SimulatePatientCovariates,  cSimCovariates,  nQtyOfPatients = nQtyPatsToSimulate ) )
    # repeat
    # {
    #     dfCovRet[ , iCov] = SimulatePatientCovariates( cSimCovariates[[ iCov ]], nQtyPats  )
    #
    #     if( iCov == nQtyCovs )
    #         break
    #     iCov = iCov + 1
    #
    # }
    names(dfCovRet) <- paste( "vCov", 1:nQtyCovs, sep="")
    return( dfCovRet )
}

SimulateAllPatientCovariates.NULL <- function( cSimCovariates,  cTrialDesign   )
{

    return( NULL )
}