diagnostic.bcdpmeta function

Diagnostic function for bcdpmeta object in jarbes

This function performers an approximated Bayesian cross-validation for a bcmeta object and specially designed diagnostics to detect the existence of a biased component.

## S3 method for class 'bcdpmeta'
diagnostic(
  object,
  post.p.value.cut = 0.05,
  study.names = NULL,
  size.forest = 0.4,
  lwd.forest = 0.2,
  shape.forest = 23,
  bias.plot = TRUE,
  cross.val.plot = FALSE,
  level = c(0.5, 0.75, 0.95),
  x.lim = c(0, 1),
  y.lim = c(0, 10),
  x.lab = "P(Bias)",
  y.lab = "Mean Bias",
  title.plot = paste("Bias Diagnostics Contours (50%, 75% and 95%)"),
  kde2d.n = 25,
  marginals = TRUE,
  bin.hist = 30,
  color.line = "black",
  color.hist = "white",
  color.data.points = "black",
  alpha.data.points = 0.1,
  S = 5000,
  ...
)

Arguments

• object: The object generated by the function b3lmeta.
• post.p.value.cut: Posterior p-value cut point to assess outliers.
• study.names: Character vector containing names of the studies used.
• size.forest: Size of the center symbol mark in the forest-plot lines
• lwd.forest: Thickness of the lines in the forest-plot
• shape.forest: Type of symbol for the center mark in the forest-plot lines
• bias.plot: Display the bias plot. The default is TRUE.
• cross.val.plot: Display the cross validation plot. The default is FALSE.
• level: Vector with the probability levels of the contour plot. The default values are: 0.5, 0.75, and 0.95.
• x.lim: Numeric vector of length 2 specifying the x-axis limits.
• y.lim: Numeric vector of length 2 specifying the y-axis limits.
• x.lab: Text with the label of the x-axis.
• y.lab: Text with the label of the y-axis.
• title.plot: Text for setting a title in the bias plot.
• kde2d.n: The number of grid points in each direction for the non-parametric density estimation. The default is 25.
• marginals: If TRUE the marginal histograms of the posteriors are added to the plot.
• bin.hist: The number of bins in for the histograms. The default value is 30.
• color.line: The color of the contour lines. The default is "black.
• color.hist: The color of the histogram bars. The default is "white".
• color.data.points: The color of the data points. The default is "black".
• alpha.data.points: Transparency of the data points.
• S: The number of sample values from the joint posterior distribution used to approximate the contours. The default is S=5000.
• ...: ...