pr_eoi | R Documentation |
Calculate Pr(effect_dose - effect_reference_dose > EOI | data) or Pr(effect_dose > EOI | data).
pr_eoi(x, eoi, dose, reference_dose = NULL, time = NULL)
x |
output from a call to |
eoi |
a vector of the effects of interest (EOI) in the probability function. |
dose |
a vector of the doses for which to calculate the posterior probabilities. |
reference_dose |
a vector of doses for relative effects of interest. |
time |
the time at which to calculate the posterior quantity. Defaults to the latest timepoint. Applies to longitudinal models only. |
A tibble listing the doses, times, and
Pr(effect_dose - effect_reference_dose > eoi) if reference_dose
is specified; otherwise, Pr(effect_dose > eoi).
set.seed(888) data <- dreamer_data_linear( n_cohorts = c(20, 20, 20), dose = c(0, 3, 10), b1 = 1, b2 = 3, sigma = 5 ) # Bayesian model averaging output <- dreamer_mcmc( data = data, n_adapt = 1e3, n_burn = 1e3, n_iter = 1e4, n_chains = 2, silent = FALSE, mod_linear = model_linear( mu_b1 = 0, sigma_b1 = 1, mu_b2 = 0, sigma_b2 = 1, shape = 1, rate = .001, w_prior = 1 / 2 ), mod_quad = model_quad( mu_b1 = 0, sigma_b1 = 1, mu_b2 = 0, sigma_b2 = 1, mu_b3 = 0, sigma_b3 = 1, shape = 1, rate = .001, w_prior = 1 / 2 ) ) pr_eoi(output, dose = 3, eoi = 10) # difference of two doses pr_eoi(output, dose = 3, eoi = 10, reference_dose = 0) # single model pr_eoi(output$mod_linear, dose = 3, eoi = 10)
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