empty_data <- DataDA(doseGrid = c(
0.1, 0.5, 1, 1.5, 3, 6,
seq(from = 10, to = 80, by = 2)
), Tmax = 60)
npiece <- 10
t_max <- 60
lambda_prior <- function(k) {
npiece / (t_max * (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
)
my_increments <- IncrementsRelative(
intervals = c(0, 20),
increments = c(1, 0.33)
)
my_next_best <- NextBestNCRM(
target = c(0.2, 0.35),
overdose = c(0.35, 1),
max_overdose_prob = 0.25
)
my_size1 <- CohortSizeRange(
intervals = c(0, 30),
cohort_size = c(1, 3)
)
my_size2 <- CohortSizeDLT(
intervals = c(0, 1),
cohort_size = c(1, 3)
)
my_size <- maxSize(my_size1, my_size2)
my_stopping1 <- StoppingTargetProb(
target = c(0.2, 0.35),
prob = 0.5
)
my_stopping2 <- StoppingMinPatients(nPatients = 50)
my_stopping <- (my_stopping1 | my_stopping2)
my_safety_window <- SafetyWindowConst(c(6, 2), 7, 7)
design <- DADesign(
model = model,
increments = my_increments,
nextBest = my_next_best,
stopping = my_stopping,
cohort_size = my_size,
data = empty_data,
safetyWindow = my_safety_window,
startingDose = 3
)
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