Simulate outcomes from a hierarchical CRM design

Usage

# S4 method for class '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(),
  ...
)

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

Value

an object of class HierarchicalSimulations.