dlt_rate function

Evaluation of the DLT rate

Calculate the DLT rate for each trial, the average DLT rate, the percent of trials which have $DLT rate > target_rate + margin$, the percent of trials which have $DLT rate < target_rate - margin$ and the percent of trials which have $target_rate - margin < DLT rate < target_rate + margin$.

dlt_rate(
  dlt_matrix,
  trial = FALSE,
  target_rate = NULL,
  margin = NULL,
  digits = 2
)

Arguments

• dlt_matrix: a matrix of the number of DLT for each step of the trial (column) and for each trial (row).
• trial: a logical value indicating if the DLT rate for each trial should be returned.
• target_rate: a numerical value of the target rate of DLT.
• margin: a numerical value of the acceptable distance from the target_rate.
• digits: a numerical value indicating the number of digits.

Returns

trial a numerical vector of the DLT rate for each trial.

average a numerical value of the average of DLT rate considering a batch of trials.

upper the percent of trials which the DLT rate > target_rate + margin if margin != NULL and target_rate != NULL.

lower the percent of trials which the DLT rate < target_rate - margin if margin != NULL and target_rate != NULL.

interval the percent of trials which the target_rate - margin < DLT rate < target_rate + margin if margin != NULL and target_rate != NULL.

Examples

## Not run:

DLT <- 0
dose <- 20
step_zero <- ewoc_d1classical(DLT ~ dose, type = 'discrete',
                           theta = 0.33, alpha = 0.25,
                           min_dose = 0, max_dose = 100,
                           dose_set = seq(0, 100, 20),
                           rho_prior = matrix(1, ncol = 2, nrow = 1),
                           mtd_prior = matrix(1, ncol = 2, nrow = 1),
                           rounding = "nearest")
stop_rule_sim(step_zero)
response_sim <- response_d1classical(rho = 0.05, mtd = 20, theta = 0.33,
                                  min_dose = 10, max_dose = 50)
sim <- ewoc_simulation(step_zero = step_zero,
                       n_sim = 1, sample_size = 2,
                       alpha_strategy = "increasing",
                       response_sim = response_sim,
                       stop_rule_sim = stop_rule_sim,
                       ncores = 2)
dlt_rate(sim$dlt_sim)
## End(Not run)

## Not run:

DLT <- 0
dose <- 20
step_zero <- ewoc_d1classical(DLT ~ dose, type = 'discrete',
                           theta = 0.33, alpha = 0.25,
                           min_dose = 0, max_dose = 100,
                           dose_set = seq(0, 100, 20),
                           rho_prior = matrix(1, ncol = 2, nrow = 1),
                           mtd_prior = matrix(1, ncol = 2, nrow = 1),
                           rounding = "nearest")
stop_rule_sim(step_zero)
response_sim <- response_d1classical(rho = 0.05, mtd = 20, theta = 0.33,
                                  min_dose = 10, max_dose = 50)
sim <- ewoc_simulation(step_zero = step_zero,
                       n_sim = 2, sample_size = 30,
                       alpha_strategy = "increasing",
                       response_sim = response_sim,
                       stop_rule_sim = stop_rule_sim,
                       ncores = 2)
dlt_rate(sim$dlt_sim)
## End(Not run)