DualResponsesDesign-class | R Documentation |

`LogisticIndepBeta`

model
model and efficacy responses using `ModelEff`

model class
without DLE and efficacy samples. It contain all slots in
`RuleDesign`

and `TDDesign`

class objectThis is a class of design based on DLE responses using the `LogisticIndepBeta`

model
model and efficacy responses using `ModelEff`

model class
without DLE and efficacy samples. It contain all slots in
`RuleDesign`

and `TDDesign`

class object

`data`

the data set of

`DataDual`

class object`Effmodel`

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

`ModelEff`

##Construct the DualResponsesDesign 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 ##The DLE model must be of 'ModelTox' (e.g 'LogisticIndepBeta') class DLEmodel <- LogisticIndepBeta(binDLE=c(1.05,1.8), DLEweights=c(3,3), DLEdose=c(25,300), data=data) ##The efficacy model of 'ModelEff' (e.g 'Effloglog') class Effmodel<-Effloglog(Eff=c(1.223,2.513),Effdose=c(25,300), nu=c(a=1,b=0.025),data=data,c=0) ##The escalation rule using the 'NextBestMaxGain' class mynextbest<-NextBestMaxGain(DLEDuringTrialtarget=0.35, DLEEndOfTrialtarget=0.3) ##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 <- DualResponsesDesign(nextBest=mynextbest, model=DLEmodel, Effmodel=Effmodel, stopping=myStopping, increments=myIncrements, cohortSize=mySize, data=data,startingDose=25)

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