pr_med {dreamer}

Pr(minimum efficacious dose)

Description

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).

Usage

pr_med(
  x,
  doses = attr(x, "doses"),
  csd = NULL,
  reference_dose = NULL,
  greater = TRUE,
  time = NULL
)

Arguments

x

output from a call to dreamer_mcmc().

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 reference_dose is specified, this function calculates the posterior probability that each dose is the smallest dose such that (effect_dose - effect_reference_dose > CSD).

greater

if TRUE, higher responses indicate better efficacy. If FALSE, lower responses indicate better efficacy.'

time

the time (scalar) at which the Pr(MED) should be calculated. Applies only to longitudinal models.

Value

A tibble listing each dose and the posterior probability that each dose is the minimum efficacious dose.

Examples

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)