examples/Rules-method-nextBest-NextBestTDsamples.R

In Roche/crmPack: Object-Oriented Implementation of CRM Designs

# Example of usage for `NextBestTDsamples` NextBest class.
my_data <- Data(
  x = c(25, 50, 50, 75, 150, 200, 225, 300),
  y = c(0, 0, 0, 0, 1, 1, 1, 1),
  ID = 1:8,
  cohort = c(1L, 2L, 2L, 3L, 4L, 5L, 6L, 7L),
  doseGrid = seq(from = 25, to = 300, by = 25)
)

my_model <- LogisticIndepBeta(
  binDLE = c(1.05, 1.8),
  DLEweights = c(3, 3),
  DLEdose = c(25, 300),
  data = my_data
)

# Set-up some MCMC parameters and generate samples.
my_options <- McmcOptions(burnin = 100, step = 2, samples = 800)
my_samples <- mcmc(my_data, my_model, my_options)

# Target probabilities of the occurrence of a DLT during trial and
# at the end of the trial are defined as 0.35 and 0.3, respectively.
# 'derive' is specified such that the 30% posterior quantile of the TD35 and
# TD30 samples will be used as TD35 and TD30 estimates.
tds_next_best <- NextBestTDsamples(
  prob_target_drt = 0.35,
  prob_target_eot = 0.3,
  derive = function(samples) {
    as.numeric(quantile(samples, probs = 0.3))
  }
)

# doselimit is the maximum allowable dose level to be given to subjects.
dose_recommendation <- nextBest(
  nextBest = tds_next_best,
  doselimit = max(my_data@doseGrid),
  samples = my_samples,
  model = my_model,
  data = my_data
)

dose_recommendation$next_dose_drt
dose_recommendation$plot