examples/design-class-TDsamplesDesign.R

##Specified the design to run simulations
##The design comprises a model, the escalation rule, starting data, 
##a cohort size and a starting dose
##Define your data set first using an empty data set 
## with dose levels from 25 to 300 with increments 25
data <- Data(doseGrid=seq(25,300,25))

##The design only incorporate DLE responses and DLE samples are involved
##Specified the model of 'ModelTox' class eg 'LogisticIndepBeta' class model
model<-LogisticIndepBeta(binDLE=c(1.05,1.8),DLEweights=c(3,3),DLEdose=c(25,300),data=data)

samples <- mcmc(data=data, model=model, options=McmcOptions(burnin=100,step=2,samples=200))
##Then the escalation rule
tdNextBest<-NextBestTDsamples(targetDuringTrial=0.35,targetEndOfTrial=0.3,
                              derive=function(TDsamples){quantile(TDsamples,probs=0.3)})
## The cohort size, size of 3 subjects
mySize <-CohortSizeConst(size=3)
##Deifne the increments for the dose-escalation process
##The maximum increase of 200% for doses up to the maximum of the dose specified in the doseGrid
##The maximum increase of 200% for dose above the maximum of the dose specified in the doseGrid
##This is to specified a maximum of 3-fold restriction in dose-esclation
myIncrements<-IncrementsRelative(intervals=c(min(data@doseGrid),max(data@doseGrid)), 
                                 increments=c(2,2))
##Specified the stopping rule e.g stop when the maximum sample size of 36 patients has been reached
myStopping <- StoppingMinPatients(nPatients=36)
##Now specified the design with all the above information and starting with a dose of 25
design <- TDsamplesDesign(model=model,
                          nextBest=tdNextBest,
                          stopping=myStopping,
                          increments=myIncrements,
                          cohortSize=mySize,
                          data=data,startingDose=25)
0liver0815/onc-crmpack-test documentation built on Feb. 19, 2022, 12:25 a.m.