Examples/example1.R

In eniclas/FAIRsimulator: Simulation Platform for the FAIR Trial

## This example simulates a three age cohort design

library(FAIRsimulator)

set.seed(32423)

probTemperation <- function(probs) {
  probs <- sqrt(probs)/sum(sqrt(probs))
  return(probs)
}

StudyObj <- createStudy(latestTimeForNewBirthCohorts=18*30,studyStopTime = 32*30,
                        nSubjects = c(320,320,320),
                        randomizationProbabilities = list(rep(0.20,5),rep(0.20,5),rep(0.20,5)),
                        minAllocationProbabilities = list(c(0.2,rep(0,4)),c(0.2,rep(0,4)),c(0.2,rep(0,4))),
                        treatments =list(c("SoC-1","TRT-1","TRT-2","TRT-3","TRT-4"),c("SoC-2","TRT-5","TRT-6","TRT-7","TRT-8"),c("SoC-3","TRT-9","TRT-10","TRT-11","TRT-12")),
                        effSizes = list(c(0,0.05,0.1,0.15,0.25),c(0,0.05,0.1,0.15,0.25),c(0,0.05,0.1,0.15,0.25)),
                        Recruitmentfunction=function(...) {return(5000)},
                        accumulatedData =TRUE,
                        probTemperationFunction = probTemperation)



StudyObj<-AdaptiveStudy(StudyObj)

## Plot the design
plotStudyCohorts(StudyObj)

## plot the number of active subjects per treatment cycle and cohort
plotActiveSubjects(StudyObj)

## Plot the HAZ profiles versus age.
plotHAZ(StudyObj)

## Plot the HAZ data and the treatment effects
plotHAZTreatmentEff(StudyObj)

# Plot the randomization probabilities over time
plotProbs(StudyObj)

## Extract the probabilities used in the plotProbs plot above.
#tmp <- getProbData(StudyObj)