DualDesign-class | R Documentation |
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 class
DualEndpoint
data
what is the dose grid, any previous data, etc., contained
in an object of class DataDual
Note that the NextBest
slot can be of any class, this allows for easy
comparison with recommendation methods that don't use the
biomarker information.
# Define the dose-grid
emptydata <- DataDual(doseGrid = c(1, 3, 5, 10, 15, 20, 25, 40, 50, 80, 100))
# Initialize the CRM model
model <- DualEndpointRW(mu = c(0, 1),
Sigma = matrix(c(1, 0, 0, 1), nrow=2),
sigma2betaW = 0.01,
sigma2W = c(a=0.1, b=0.1),
rho = c(a=1, b=1),
smooth="RW1")
# Choose the rule for selecting the next dose
myNextBest <- NextBestDualEndpoint(target=c(0.9, 1),
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
myStopping4 <- StoppingTargetBiomarker(target=c(0.9, 1),
prob=0.5)
myStopping <- myStopping4 | StoppingMinPatients(40)
# Choose the rule for dose increments
myIncrements <- IncrementsRelative(intervals=c(0, 20),
increments=c(1, 0.33))
# Initialize the design
design <- DualDesign(model = model,
data = emptydata,
nextBest = myNextBest,
stopping = myStopping,
increments = myIncrements,
cohortSize = mySize,
startingDose = 3)
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