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Average marginal MCMC draws across time points.

Source: R/brm_marginal_draws_average.R
brm_marginal_draws_average.Rd

Simple un-weighted arithmetic mean of marginal MCMC draws across time points.

Usage

brm_marginal_draws_average(data, draws, times = NULL, label = "average")

Arguments

data

A classed data frame from brm_data(), or an informative prior archetype from a function like brm_archetype_successive_cells().

draws

List of posterior draws from brm_marginal_draws().

times

Character vector of discrete time point levels over which to average the MCMC samples within treatment group levels. Set to NULL to average across all time points. Levels are automatically sanitized with make.names(unique = FALSE, allow_ = TRUE) to ensure agreement with brms variable names in downstream computations.

label

Character of length 1, time point label for the averages. Automatically sanitized with make.names(unique = FALSE, allow_ = TRUE). Must not conflict with any existing time point labels in the data after the label and time points are sanitized.

Value

A named list of tibbles of MCMC draws of the marginal posterior distribution of each treatment group and time point (or group-by-subgroup-by-time, if applicable). In each tibble, there is 1 row per posterior sample sand one column for each type of marginal distribution (i.e. each combination of treatment group and discrete time point. The specific tibbles in the returned list are described below:

  • response: on the scale of the response variable.

  • difference_time: change from baseline: the response at a particular time minus the response at baseline (reference_time). Only returned if the role argument of brm_data() was "response". (If role is "change", then response already represents change from baseline.)

  • difference_group: treatment effect: the the difference_time at each active group minus the difference_time at the control group (reference_group). If role is "change", then treatment group is instead the difference between response at each active group minus the response at the control group.

  • difference_subgroup: subgroup differences: the difference_group at each subgroup level minus the difference_group at the subgroup reference level (reference_subgroup).

Separation string

Post-processing in brm_marginal_draws() names each of the group-by-time marginal means with the delimiting character string from Sys.getenv("BRM_SEP", unset = "|"). Neither the column names nor element names of the group and time variables can contain this string. To set a custom string yourself, use Sys.setenv(BRM_SEP = "YOUR_CUSTOM_STRING").

See also

Other marginals: brm_marginal_data(), brm_marginal_draws(), brm_marginal_grid(), brm_marginal_probabilities(), 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",
  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)
brm_marginal_draws_average(draws = draws, data = data)
brm_marginal_draws_average(
  draws = draws,
  data = data,
  times = c("time_1", "time_2"),
  label = "mean"
)
}