Get a vector of logical values reflecting whether each dose is admissible. Admissibility is defined in different ways for different models, and may not be defined at all in some models. For instance, in the TPI method, doses are inadmissible when the posterior probability is high that the toxicity rate exceeds the target value. In contrast, admissibility is not defined in the general CRM model (but it can be added with auxiliary classes). In this latter case, doses are implicitly considered to be admissible, by default.
dose_admissible(x, ...)Object of class selector
arguments passed to other methods
a logical vector
outcomes <- '1NNN 2TTT'
# TPI example. This method defines admissibility.
fit1 <- get_tpi(num_doses = 5, target = 0.3, k1 = 1, k2 = 1.5,
exclusion_certainty = 0.95) %>%
fit(outcomes)
fit1 %>% dose_admissible()
#> [1] TRUE FALSE FALSE FALSE FALSE
# Ordinary CRM example with no admissibility function.
skeleton <- c(0.05, 0.1, 0.25, 0.4, 0.6)
target <- 0.25
fit2 <- get_dfcrm(skeleton = skeleton, target = target) %>%
fit(outcomes)
fit2 %>% dose_admissible()
#> [1] TRUE TRUE TRUE TRUE TRUE
# Same CRM example with added admissibility function
fit3 <- get_dfcrm(skeleton = skeleton, target = target) %>%
stop_when_too_toxic(dose = 1, tox_threshold = target, confidence = 0.8) %>%
fit(outcomes)
fit3 %>% dose_admissible()
#> [1] TRUE FALSE FALSE FALSE FALSE