diagnostic.bcmeta {jarbes}

Diagnostic function for bcmeta object in jarbes

Description

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

Usage

## S3 method for class 'bcmeta'
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 = TRUE,
  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 TRUE.

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.

...

...