crmPack (version 1.0.6)

DualResponsesSamplesDesign-class: This is a class of design based on DLE responses using the LogisticIndepBeta model model and efficacy responses using ModelEff model class with DLE and efficacy samples.It contain all slots in RuleDesign and TDsamplesDesign class object

Description

This is a class of design based on DLE responses using the LogisticIndepBeta model model and efficacy responses using ModelEff model class with DLE and efficacy samples.It contain all slots in RuleDesign and TDsamplesDesign class object

Slots

data

the data set of DataDual class object

Effmodel

the pseudo efficacy model to be used, an object class of ModelEff

Examples

##Construct the DualResponsesSamplesDesign for simulations
##The design comprises the DLE and efficacy models, 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 <- DataDual(doseGrid=seq(25,300,25),placebo=FALSE)

## First for the DLE model and DLE samples
## The DLE model must be of 'ModelTox' 
## (e.g 'LogisticIndepBeta') class and 
## DLEsamples of 'Samples' class
options<-McmcOptions(burnin=100,step=2,samples=200)
DLEmodel <- LogisticIndepBeta(binDLE=c(1.05,1.8),DLEweights=c(3,3),
                              DLEdose=c(25,300),data=data)
DLEsamples<-mcmc(data,DLEmodel,options)
##The efficacy model of 'ModelEff' (e.g 'Effloglog') class and the efficacy samples
Effmodel<-Effloglog(Eff=c(1.223,2.513),Effdose=c(25,300),nu=c(a=1,b=0.025),data=data,c=0)
Effsamples<-mcmc(data,Effmodel,options)
##The escalation rule using the 'NextBestMaxGainSamples' class
mynextbest<-NextBestMaxGainSamples(DLEDuringTrialtarget=0.35,
                                   DLEEndOfTrialtarget=0.3,
                                   TDderive=function(TDsamples){
                                     quantile(TDsamples,prob=0.3)},
                                   Gstarderive=function(Gstarsamples){
                                     quantile(Gstarsamples,prob=0.5)})


##The increments (see Increments class examples) 
## 200% allowable increase for dose below 300 and 200% increase for dose above 300
myIncrements<-IncrementsRelative(intervals=c(25,300),
                                 increments=c(2,2))
##cohort size of 3
mySize<-CohortSizeConst(size=3)
##Stop only when 36 subjects are treated
myStopping <- StoppingMinPatients(nPatients=36)
##Now specified the design with all the above information and starting with a dose of 25

design <- DualResponsesSamplesDesign(nextBest=mynextbest,
                                     cohortSize=mySize,
                                     startingDose=25,
                                     model=DLEmodel,
                                     Effmodel=Effmodel,
                                     data=data,
                                     stopping=myStopping,
                                     increments=myIncrements)