This class has special requirements for the model
and data
slots in comparison to the parent class Design
:
model
the model to be used, an object of or inheriting from class
Model
, see in particular
DALogisticLogNormal
and
TITELogisticLogNormal
which make use of the
time-to-DLT data
data
what is the dose grid, any previous data, etc., contained
in an object of class DataDA
safetyWindow
still to be documented.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | # nolint start
# Define the dose-grid and PEM parameters
emptydata <- DataDA(doseGrid=c(0.1, 0.5,1, 1.5, 3, 6,
seq(from=10, to=80, by=2)),Tmax=60)
# Initialize the mDA-CRM model
npiece_=10
Tmax_=60
lambda_prior<-function(k){
npiece_/(Tmax_*(npiece_-k+0.5))
}
model<-DALogisticLogNormal(mean=c(-0.85,1),
cov=matrix(c(1,-0.5,-0.5,1),nrow=2),
ref_dose=56,
npiece=npiece_,
l=as.numeric(t(apply(as.matrix(c(1:npiece_),1,npiece_),2,lambda_prior))),
C_par=2)
# Choose the rule for dose increments
myIncrements <- IncrementsRelative(intervals=c(0,20),
increments=c(1,0.33))
# Choose the rule for selecting the next dose
nextMaxDose <- maxDose(myIncrements,data=emptydata)
myNextBest <- NextBestNCRM(target=c(0.2,0.35),
overdose=c(0.35,1),
maxOverdoseProb=0.25)
# Choose the rule for the cohort-size
mySize1 <- CohortSizeRange(intervals=c(0, 30),
cohortSize=c(1, 3))
mySize2 <- CohortSizeDLT(DLTintervals=c(0, 1),
cohortSize=c(1, 3))
mySize <- maxSize(mySize1, mySize2)
# Choose the rule for stopping
myStopping1 <- StoppingTargetProb(target=c(0.2, 0.35),
prob=0.5)
myStopping2 <- StoppingMinPatients(nPatients=50)
myStopping <- (myStopping1 | myStopping2)
# Choose the safety window
mysafetywindow=SafetyWindowConst(c(6,2),7,7)
# Initialize the design
design <- DADesign(model=model,
increments=myIncrements,
nextBest=myNextBest,
stopping=myStopping,
cohortSize=mySize,
data=emptydata,
safetyWindow=mysafetywindow,
startingDose=3)
# nolint end
|
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