Plots marginal estimates of a fitted RoBMA regression object

marginal_plot allows to visualize prior and posterior distributions of marginal estimates of a RoBMA regression model.

Usage

marginal_plot(
  x,
  parameter,
  conditional = FALSE,
  plot_type = "base",
  prior = FALSE,
  output_scale = NULL,
  dots_prior = NULL,
  ...
)

x: a fitted RoBMA regression object
parameter: regression parameter to be plotted
conditional: whether conditional marginal estimates should be plotted. Defaults to FALSE which plots the model-averaged estimates.
plot_type: whether to use a base plot "base" or ggplot2 "ggplot" for plotting. Defaults to "base".
prior: whether prior distribution should be added to figure. Defaults to FALSE.
output_scale: transform the effect sizes and the meta-analytic effect size estimate to a different scale. Defaults to NULL which returns the same scale as the model was estimated on.
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.

plot.RoBMA returns either NULL if plot_type = "base" or an object object of class 'ggplot2' if plot_type = "ggplot2".