escalation (version 0.2.3)

prob_tox_exceeds.boin_comb_selector: Probability that the toxicity rate exceeds some threshold.

Description

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.

Usage

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

Value

numerical vector of probabilities

numerical vector of probabilities

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

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)
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)