NextBestTDsamples-class: 'NextBestTDsamples'

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

NextBestTDsamples

Description

NextBestTDsamples is the class to find a next best dose based on Pseudo DLT model with samples. Namely, it is to find two next best doses, one for allocation during the trial and the second for final recommendation at the end of a trial. Hence, there are two target probabilities of the occurrence of a DLT that must be specified: target probability to be used during the trial and target probability to be used at the end of the trial.

Usage

NextBestTDsamples(prob_target_drt, prob_target_eot, derive)

.DefaultNextBestTDsamples()

Arguments

prob_target_drt	(proportion) see slot definition in NextBestTD.
prob_target_eot	(proportion) see slot definition in NextBestTD.
derive	(function) see slot definition.

Slots

derive

(function)
derives, based on a vector of posterior dose samples, the target dose that has the probability of the occurrence of DLT equals to either the prob_target_drt or prob_target_eot. It must therefore accept one and only one argument, which is a numeric vector, and return a number.

Note

Typically, end users will not use the .DefaultNextBestTDsamples() function.

Examples

# Target probability of the occurrence of a DLT during the trial is set to 0.35.
# Target probability of the occurrence of a DLT at the end of the trial is set to 0.3.
# We want the use the 30% posterior quantile (the 30th percentile) of the TD35
# (the dose level with probability of the DLT equals 0.35) and TD30 samples.
my_next_best <- NextBestTDsamples(
  prob_target_drt = 0.35,
  prob_target_eot = 0.3,
  derive = function(samples) {
    as.numeric(quantile(samples, probs = 0.3))
  }
)

Roche/crmPack documentation built on April 30, 2024, 3:19 p.m.