Create Z-Curve Meta-Analytic Plot

Plots a fitted zcurve_RoBMA object, visualizing the z-curve, model fit, extrapolation, and credible intervals.

Usage

# S3 method for class 'zcurve_RoBMA'
plot(
  x,
  conditional = FALSE,
  plot_type = "base",
  probs = c(0.025, 0.975),
  max_samples = 500,
  plot_fit = TRUE,
  plot_extrapolation = TRUE,
  plot_CI = TRUE,
  plot_thresholds = TRUE,
  from = -6,
  to = 6,
  by.hist = 0.5,
  length.out.hist = NULL,
  by.lines = 0.05,
  length.out.lines = NULL,
  dots_hist = NULL,
  dots_extrapolation = NULL,
  dots_thresholds = NULL,
  ...
)

Arguments

x: A zcurve_RoBMA object to be plotted.
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 posterior samples to use for plotting credible intervals. Defaults to 500.
plot_fit: Should the model fit be included in the plot? Defaults to TRUE.
plot_extrapolation: Should model extrapolation be included in the plot? Defaults to TRUE.
plot_CI: Should credible intervals be included in the plot? Defaults to TRUE.
plot_thresholds: Should significance thresholds be displayed 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.hist: Bin width for the histogram of observed z-values. Defaults to 0.5.
length.out.hist: Number of bins for the histogram. If NULL, determined by by.hist. Defaults to NULL.
by.lines: Step size for plotting model fit and extrapolation lines. Defaults to 0.05.
length.out.lines: Number of points for plotting lines. If NULL, determined by by.lines. Defaults to NULL.
dots_hist: List of additional graphical parameters for the histogram. For base R: border, col, density, angle. For ggplot2: color, fill, alpha.
dots_extrapolation: List of additional graphical parameters for the extrapolation line/ribbon. For base R lines: lwd, col, lty. For base R ribbon: col (will be alpha-blended), border. For ggplot2 lines: linewidth, color, linetype. For ggplot2 ribbon: fill, alpha.
dots_thresholds: List of additional graphical parameters for the threshold lines. For base R: col, lty, lwd. For ggplot2: color, linetype, linewidth.
...: Additional graphical arguments for the main fit line and ribbon (passed to lines.zcurve_RoBMA), as well as basic plotting arguments. For base R lines: lwd, col, lty. For base R ribbon: col (will be alpha-blended), border. For ggplot2 lines: linewidth, color, linetype. For ggplot2 ribbon: fill, alpha. Basic plotting arguments (both base R and ggplot2): xlab (x-axis label, default: "Z-Statistic"), ylab (y-axis label, default: "Density"), main (plot title, default: ""), ylim (y-axis limits). For base R only: xaxt (x-axis type, default: "s"), yaxt (y-axis type, default: "s").

Value

Returns NULL if plot_type = "base", or a ggplot2 object if plot_type = "ggplot2".

Examples

if (FALSE) { # \dontrun{
# using the example data from Anderson et al. 2010 and fitting the default model
# (note that the model can take a while to fit)
fit <- RoBMA(r = Anderson2010$r, n = Anderson2010$n,
             study_names = Anderson2010$labels, algorithm = "ss")

zcurve_fit <- as_zcurve(fit)
plot(zcurve_fit)
} # }

Usage

Arguments

Value

See also

Examples