Prepare brma Data for metafor Forest Plots — as_metafor

as_metafor_forest extracts observed effect sizes, standard errors, study labels, and RoBMA posterior summary intervals in a structure that can be passed to metafor's forest plotting functions.

Usage

as_metafor_forest(x, ...)

# S3 method for class 'brma'
as_metafor_forest(
  x,
  level = 95,
  addpred = FALSE,
  newdata = NULL,
  bias_adjusted = TRUE,
  conditional = FALSE,
  ...
)

Arguments

x: a fitted brma object.
...: additional named arguments stored in forest_args and later passed to forest.default. Shared graphical arguments are also stored in addpoly_args. This includes metafor's auxiliary-column arguments ilab, ilab.lab, ilab.xpos, and ilab.pos.
level: credible/confidence level in percent, greater than 0 and less than 100. A value below 1 is read as a proportion (0.95 is 95 percent), so 1 means 1 percent. Defaults to 95.
addpred: logical; whether to compute a marginal posterior prediction interval for one new true effect. Defaults to FALSE.
newdata: optional one-row prediction design used when addpred = TRUE. When omitted, the interval is evaluated at the average expanded design using pooled_effect(). When supplied, each row passed to predict.brma() is one new true effect; with bias_adjusted = FALSE, it targets a selected new publication. The pooled reference declares no new-publication SE or selection event. The forest adapter accepts exactly one because it draws one summary polygon.
bias_adjusted: logical; whether pooled and prediction summaries should adjust for publication bias. Defaults to TRUE.
conditional: logical; whether to return conditional posterior summaries for RoBMA product-space objects. Defaults to FALSE.

Value

A list of class metafor_forest.brma with study-level data, pooled posterior summaries, and ready-to-use argument lists for forest.default and addpoly.default. The forest_args include enough vertical space for the default summary row. The returned object can also be plotted directly with forest.

Examples

if (FALSE) { # \dontrun{
if (requireNamespace("metadat", quietly = TRUE) &&
    requireNamespace("metafor", quietly = TRUE)) {
  data(dat.bcg, package = "metadat")
  dat <- metafor::escalc(
    measure = "RR",
    ai      = tpos,
    bi      = tneg,
    ci      = cpos,
    di      = cneg,
    data    = dat.bcg
  )

  fit <- brma(yi = yi, vi = vi, data = dat, measure = "RR")
  count_columns <- as.matrix(dat[, c("tpos", "tneg", "cpos", "cneg")])
  forest_data <- as_metafor_forest(
    fit,
    addpred   = TRUE,
    slab      = paste(dat$author, dat$year),
    ilab      = count_columns,
    ilab.lab  = c("T+", "T-", "C+", "C-"),
    ilab.xpos = c(-7, -6, -5, -4),
    xlim      = c(-10, 4),
    atransf   = exp
  )
  metafor::forest(forest_data, predstyle = "bar")

  # Or draw the metafor calls directly:
  do.call(metafor::forest.default, forest_data$forest_args)
  do.call(metafor::addpoly.default, forest_data$addpoly_args)
}
} # }