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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