RoBMA (version 4.0.0)

plot.brma: Plots brma Object

Description

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

Usage

# S3 method for 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,
  ...
)

Value

plot.brma returns either NULL if plot_type = "base"

or a ggplot2 object if plot_type = "ggplot".

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.

See Also

RoBMA()

Examples

if (FALSE) {
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")
}
}