brm_marginal_draws_average {brms.mmrm}

Average marginal MCMC draws across time points.

Description

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

Usage

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

Arguments

draws

List of posterior draws from brm_marginal_draws().

data

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

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). See brm_marginal_draws() for the full details of the return value. The only difference is that brm_marginal_draws_average() returns a single pseudo-time-point to represent the average across multiple real time points.

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",
  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"
)
}