plot.brma: Plots brma Object

In RoBMA: Robust Bayesian Meta-Analyses

Plots brma Object

Description

plot.brma visualizes posterior (and prior) distribution a brma object.

Usage

## S3 method for class 'brma'
plot(
  x,
  parameter,
  parameter_mods,
  parameter_scale,
  prior = FALSE,
  standardized_coefficients = FALSE,
  conditional = FALSE,
  output_measure = NULL,
  transform = NULL,
  plot_type = "base",
  dots_prior = NULL,
  ...
)

Arguments

x	a fitted brma, BMA, or RoBMA object.
parameter	a parameter to be plotted. Defaults to "mu" for the effect size, or to the meta-regression intercept when moderators are present. Additional options are "tau", "rho" for multilevel models, "PET", "PEESE", and "omega" or "weightfunction" for selection models. Use plot_pet_peese() for PET/PEESE regression plots.
parameter_mods	character. Moderator term to plot. Use "intercept" for the adjusted effect in meta-regression models.
parameter_scale	character. Scale-regression term to plot. Use "intercept" for the heterogeneity intercept in location-scale models.
prior	whether prior distribution should be added to figure. Defaults to FALSE.
standardized_coefficients	whether to plot moderator and scale-regression coefficients on the standardized predictor scale. Defaults to FALSE.
conditional	whether to plot the conditional posterior distribution for RoBMA product-space objects. Defaults to FALSE.
output_measure	effect-size measure for location/effect predictions. Defaults to the fitted measure. Supported conversions are among "SMD", "COR", "ZCOR", and "OR"; "RR", "HR", "IRR", "RD", and "GEN" can only be returned on their fitted measure. Use transform = "EXP" for ratio-scale output from log-scale measures.
transform	optional display transformation. Currently "EXP" exponentiates log-scale measures "OR", "RR", "HR", and "IRR".
plot_type	whether to use a base plot "base" or ggplot2 "ggplot" for plotting. Defaults to "base".
dots_prior	list of additional graphical arguments to be passed to the plotting function of the prior distribution. Supported arguments are lwd, lty, col, and col.fill, to adjust the line thickness, line type, line color, and fill color of the prior distribution respectively.
...	list of additional graphical arguments to be passed to the plotting function. Supported arguments are lwd, lty, col, col.fill, xlab, ylab, main, xlim, ylim to adjust the line thickness, line type, line color, fill color, x-label, y-label, title, x-axis range, and y-axis range respectively.

Value

plot.brma returns either NULL if plot_type = "base" or a ggplot2 object if plot_type = "ggplot".

See Also

RoBMA()

Examples

## Not run: 
if (requireNamespace("metadat", quietly = TRUE)) {
  data(dat.lehmann2018, package = "metadat")
  fit <- bPET(yi = yi, vi = vi, data = dat.lehmann2018, measure = "SMD")

  plot(fit, parameter = "mu")
  plot(fit, parameter = "tau", prior = TRUE)
  plot(fit, parameter = "PET")
}

## End(Not run)

RoBMA documentation built on May 7, 2026, 5:08 p.m.