Get the estimated mean efficacy rate at each dose under investigation. This is a set of modelled statistics. The underlying models estimate efficacy probabilities in different ways. If no model-based estimate of the mean is available, this function will return a vector of NAs.

mean_prob_eff(x, ...)

Arguments

x

Object of class selector

...

arguments passed to other methods

Value

a numerical vector

Examples

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')
mean_prob_eff(x)
#> [1] 0.2104883 0.5954319 0.9064147 0.9547711 0.9671151