crmPack (version 1.0.6)

TDsamplesDesign-class: This is a class of design based only on DLE responses using the 'LogisticIndepBeta' class model and DLE samples are also used. In addition to the slots in the more simple RuleDesign, objects of this class contain:

Description

This is a class of design based only on DLE responses using the 'LogisticIndepBeta' class model and DLE samples are also used. In addition to the slots in the more simple RuleDesign, objects of this class contain:

Slots

model

the pseudo DLE model to be used, an object class of ModelTox

stopping

stopping rule(s) for the trial, an object class of Stopping

increments

how to control increments between dose levels, an object class of Increments

PLcohortSize

rules for the cohort sizes for placebo, if any planned an object of class CohortSize

Examples

##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)