`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 |
---|---|

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 0.98459064efftox_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] 0.020 0.040 0.362 0.700 0.788