Summary statistics of the marginal posterior of an MMRM.

Summary statistics of the marginal posterior of an MMRM.

Usage

brm_marginal_summaries(draws, level = 0.95)

Arguments

draws

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

level

Numeric of length 1 between 0 and 1, credible level for the credible intervals.

Value

A tibble with one row per summary statistic and the following columns:

• marginal: type of marginal distribution. If outcome was "response" in brm_marginal_draws(), then possible values include "response" for the response on the raw scale, "change" for change from baseline, and "difference" for treatment difference in terms of change from baseline. If outcome was "change", then possible values include "response" for the response one the change from baseline scale and "difference" for treatment difference.

• statistic: type of summary statistic. "lower" and "upper" are bounds of an equal-tailed quantile-based credible interval.

• group: treatment group.

• subgroup: subgroup level, if applicable.

• time: discrete time point.

• value: numeric value of the estimate.

• mcse: Monte Carlo standard error of the estimate. The statistic column has the following possible values:

• mean: posterior mean.

• median: posterior median.

• sd: posterior standard deviation of the mean.

• lower: lower bound of an equal-tailed credible interval of the mean, with credible level determined by the level argument.

• upper: upper bound of an equal-tailed credible interval with credible level determined by the level argument.

See also

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

Examples

if (identical(Sys.getenv("BRM_EXAMPLES", unset = ""), "true")) {
set.seed(0L)
data <- brm_data(
  data = brm_simulate_simple()$data,
  outcome = "response",
  role = "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)
suppressWarnings(brm_marginal_summaries(draws))
}