`R/interface.R`

`prob_tox_exceeds.Rd`

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.

```
prob_tox_exceeds(x, threshold, ...)
prob_eff_exceeds(x, threshold, ...)
```

- x
Object of type

`selector`

- threshold
Probability that efficacy rate exceeds what?

- ...
arguments passed to other methods

numerical vector of probabilities

numerical vector of probabilities

```
# 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
```