Marginal probabilities on the treatment effect for an MMRM.

Marginal probabilities on the treatment effect for an MMRM.

Usage

brm_marginal_probabilities(draws, direction = "greater", threshold = 0)

Arguments

draws

Posterior draws of the marginal posterior obtained from brm_marginal_draws().

direction

Character vector of the same length as threshold. "greater" to compute the marginal posterior probability that the treatment effect is greater than the threshold, "less" to compute the marginal posterior probability that the treatment effect is less than the threshold. Each element direction[i] corresponds to threshold[i] for all i from 1 to length(direction).

threshold

Numeric vector of the same length as direction, treatment effect threshold for computing posterior probabilities. Each element direction[i] corresponds to threshold[i] for all i from 1 to length(direction).

Value

A tibble of probabilities of the form Prob(treatment effect > threshold | data) and/or Prob(treatment effect < threshold | data). It has one row per probability and the following columns: * group: treatment group. * subgroup: subgroup level, if applicable. * time: discrete time point, * direction: direction of the comparison in the marginal probability: "greater" for >, "less" for < * threshold: treatment effect threshold in the probability statement. * value: numeric value of the estimate of the probability.

See also

Other marginals: brm_marginal_data(), brm_marginal_draws(), brm_marginal_draws_average(), brm_marginal_grid(), brm_marginal_summaries()

Examples

if (identical(Sys.getenv("BRM_EXAMPLES", unset = ""), "true")) {
set.seed(0L)
data <- brm_data(
  data = brm_simulate_simple()$data,
  outcome = "response",
  group = "group",
  time = "time",
  patient = "patient",
  reference_group = "group_1",
  reference_time = "time_1"
)
formula <- brm_formula(
  data = data,
  baseline = FALSE,
  baseline_time = FALSE
)
tmp <- utils::capture.output(
  suppressMessages(
    suppressWarnings(
      model <- brm_model(
        data = data,
        formula = formula,
        chains = 1,
        iter = 100,
        refresh = 0
      )
    )
  )
)
draws <- brm_marginal_draws(data = data, formula = formula, model = model)
brm_marginal_probabilities(draws, direction = "greater", threshold = 0)
}