examples/Rules-method-stopTrialCIMaxGain.R

In Roche/crmPack: Object-Oriented Implementation of CRM Designs

# nolint start

##define the stopping rules based on the 'StoppingMaxGainCIRatio' class
##Using both DLE and efficacy responses
## we need a data object with doses >= 1:
data <-DataDual(x=c(25,50,25,50,75,300,250,150),
                y=c(0,0,0,0,0,1,1,0),
                w=c(0.31,0.42,0.59,0.45,0.6,0.7,0.6,0.52),
                doseGrid=seq(25,300,25),
                placebo=FALSE)

##DLEmodel must be of 'ModelTox' class
##For example, the 'logisticIndepBeta' class model
DLEmodel<-LogisticIndepBeta(binDLE=c(1.05,1.8),DLEweights=c(3,3),DLEdose=c(25,300),data=data)

##Effmodel must be  of 'ModelEff' class
##For example, the 'Effloglog' class model
Effmodel<-Effloglog(eff=c(1.223,2.513),eff_dose=c(25,300),nu=c(a=1,b=0.025),data=data)


##define the 'StoppingMaxGainCIRatio' class
myStopping <- StoppingMaxGainCIRatio(target_ratio = 5, prob_target = 0.3)
##Find the next Recommend dose using the nextBest method (plesae refer to nextbest examples)
mynextbest<-NextBestMaxGain(prob_target_drt=0.35, prob_target_eot=0.3)

RecommendDose<-nextBest(mynextbest,doselimit=max(data@doseGrid),model=DLEmodel,
                        model_eff=Effmodel,data=data)

##use 'stopTrial' to determine if the rule has been fulfilled
##use 0.3 as the target proability of DLE at the end of the trial


stopTrial(stopping=myStopping,dose=RecommendDose$next_dose,model=DLEmodel,
          data=data, Effmodel=Effmodel)

# nolint end