ewoc (version 0.3.0)

stop_rule: Evaluation of the stopping rule

Description

Calculate the average, minimum, maximum number of patients to stop a trial and the percent of stopped trials. Stopped trials contain NA after the last assigned dose.

Usage

stop_rule(dlt_matrix, sample_size, digits = 2)

Arguments

dlt_matrix

Matrix of the number of DLT for each step of the trial (column) and for each trial (row).

sample_size

a numerical value indicating the expected sample size.

digits

a numerical value indicating the number of digits.

Value

A list consisting of

• average: Average number of patients to stop a trial.

• min: Minimum number of patients to stop a trial.

• max: Maximum number of patients to stop a trial.

• nstop: Percent of stopped trials.

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