Add Lines With Posterior Predictive Distribution of Z-Statistics

Adds lines to a plot of a fitted zcurve_RoBMA object. This function is typically used to overlay additional information or model fits on an existing plot.

Usage

# S3 method for class 'zcurve_RoBMA'
lines(
  x,
  conditional = FALSE,
  plot_type = "base",
  probs = c(0.025, 0.975),
  max_samples = 500,
  extrapolate = FALSE,
  plot_CI = TRUE,
  from = -6,
  to = 6,
  by = 0.05,
  length.out = NULL,
  col = if (extrapolate) "blue" else "black",
  ...
)

Arguments

x

A RoBMA object

conditional

whether conditional estimates should be plotted. Defaults to FALSE which plots the model-averaged estimates. Note that both "weightfunction" and "PET-PEESE" are always ignoring the other type of publication bias adjustment.

plot_type

whether to use a base plot "base" or ggplot2 "ggplot" for plotting. Defaults to "base".

probs

quantiles of the posterior samples to be displayed. Defaults to c(.025, .975)

max_samples

Maximum number of samples from the posterior distribution that will be used for estimating z-curve estimates.

extrapolate

Logical indicating whether to extrapolate values beyond the observed data range.

plot_CI

Should credible intervals be included in the plot? Defaults to TRUE.

from

Lower bound of the z-value range for plotting. Defaults to -6.

to

Upper bound of the z-value range for plotting. Defaults to 6.

by

Numeric value specifying the increment for the sequence.

length.out

Optional integer specifying the desired length of the output sequence.

col

Color of the plotted line.

...

Additional graphical parameters for the line and CI ribbon. For base R lines: lwd, col, lty. For base R ribbon: alpha (alpha transparency for the ribbon). For ggplot2 lines: linewidth, color, linetype. For ggplot2 ribbon: alpha.

See also

as_zcurve(), plot.zcurve_RoBMA(), hist.zcurve_RoBMA()