simulate,HierarchicalDesign-method: Simulate outcomes from a hierarchical CRM design

Description

Usage

# S4 method for HierarchicalDesign
simulate(
  object,
  nsim = 1L,
  seed = NULL,
  truth,
  truthResponse = plogis,
  args = NULL,
  firstSeparate = FALSE,
  mcmcOptions = McmcOptions(),
  parallel = FALSE,
  nCores = min(parallel::detectCores(), 5),
  derive = list(),
  ...
)

Value

an object of class HierarchicalSimulations.

Arguments

object: the HierarchicalDesign object we want to simulate data from.
nsim: (count)
the number of simulations.
seed: see set_seed().
truth: (function or named list of function)
true DLT probability function(s). If a list is supplied, names must match the hierarchical arms.
truthResponse: (function or named list of function)
true response probability function(s).
args: (data.frame)
arguments for the truth functions.
firstSeparate: (flag)
enroll the first patient separately from the rest of the cohort? (not default) If yes, the cohort will be closed if a DLT occurs in this patient.
mcmcOptions: (McmcOptions)
object of class McmcOptions, giving the MCMC options for each evaluation in the trial. By default, the standard options are used
parallel: (flag)
should the simulation runs be parallelized across the clusters of the computer? (not default)
nCores: (count)
how many cores should be used for parallel computing? Defaults to the number of cores on the machine, maximum 5.
derive: (list)
a named list of functions which derives statistics, based on the vector of posterior MTD samples. Each list element must therefore accept one and only one argument, which is a numeric vector, and return a number.
...: not used