Probability that the toxicity rate exceeds some threshold.

Get the probability that the toxicity rate at each dose exceeds some threshold.

Get the probability that the efficacy rate at each dose exceeds some threshold.

# S3 method for class 'boin_comb_selector'
prob_tox_exceeds(x, threshold, iso = TRUE, ...)

prob_tox_exceeds(x, threshold, ...)

prob_eff_exceeds(x, threshold, ...)

Arguments

x

Object of type selector

threshold

Probability that efficacy rate exceeds what?

iso

TRUE to use isotonic regression on the posterior probabilities; FALSE to return just the posterior quantiles, which may not be monotonically increasing by dose.

...

arguments passed to other methods

Value

numerical vector of probabilities

numerical vector of probabilities

Examples

# CRM example
skeleton <- c(0.05, 0.1, 0.25, 0.4, 0.6)
target <- 0.25
outcomes <- '1NNN 2NTN'
fit <- get_dfcrm(skeleton = skeleton, target = target) %>% fit(outcomes)
# What is probability that tox rate at each dose exceeds target by >= 10%?
fit %>% prob_tox_exceeds(threshold = target + 0.1)
#> [1] 0.06487018 0.16640298 0.53408008 0.82783385 0.98459064
efftox_priors <- trialr::efftox_priors
p <- efftox_priors(alpha_mean = -7.9593, alpha_sd = 3.5487,
                   beta_mean = 1.5482, beta_sd = 3.5018,
                   gamma_mean = 0.7367, gamma_sd = 2.5423,
                   zeta_mean = 3.4181, zeta_sd = 2.4406,
                   eta_mean = 0, eta_sd = 0.2,
                   psi_mean = 0, psi_sd = 1)
real_doses = c(1.0, 2.0, 4.0, 6.6, 10.0)
model <- get_trialr_efftox(real_doses = real_doses,
                           efficacy_hurdle = 0.5, toxicity_hurdle = 0.3,
                           p_e = 0.1, p_t = 0.1,
                           eff0 = 0.5, tox1 = 0.65,
                           eff_star = 0.7, tox_star = 0.25,
                           priors = p, iter = 1000, chains = 1, seed = 2020)
x <- model %>% fit('1N 2E 3B')
prob_tox_exceeds(x, threshold = 0.45)
#> [1] 0.030 0.054 0.362 0.686 0.800