This 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`

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##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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