pr_med | R Documentation |
Calculates the posterior probability that each specified doses are the minimum effective dose in the set; i.e. the smallest dose that has a clinically significant difference (CSD).
pr_med( x, doses = attr(x, "doses"), csd = NULL, reference_dose = NULL, greater = TRUE, time = NULL )
x |
output from a call to |
doses |
the doses for which pr(MED) is to be calculated. |
csd |
the treatment effect that is clinically relevant. |
reference_dose |
a single dose that is used as the reference when
defining the MED relative to a dose (rather than in absolute terms). When
|
greater |
if |
time |
the time (scalar) at which the Pr(MED) should be calculated. Applies only to longitudinal models. |
A tibble listing each dose and the posterior probability that each dose is the minimum efficacious dose.
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 = 1e3, 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_med(output, csd = 10) # difference of two doses pr_med(output, csd = 3, reference_dose = 0) # single model pr_med(output$mod_quad, csd = 10)
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