diagnostic.hmr: Diagnostic function for hmr object in jarbes

In jarbes: Just a Rather Bayesian Evidence Synthesis

Diagnostic function for hmr object in jarbes

Description

This function performers a specially designed diagnostic for a hmr object

Usage

## S3 method for class 'hmr'
diagnostic(
  object,
  median.w = 1.5,
  study.names,
  size.forest = 0.4,
  lwd.forest = 0.2,
  shape.forest = 23,
  mu.phi = TRUE,
  mu.phi.x.lim.low = -10,
  mu.phi.x.lim.up = 10,
  colour.hist.mu.phi = "royalblue",
  colour.prior.mu.phi = "black",
  colour.posterior.mu.phi = "blue",
  title.plot.mu.phi = "Prior-to-Posterior Sensitivity",
  title.plot.weights = "Outlier Detection",
  ...
)

Arguments

object	The object generated by the function hmr.
median.w	Change colour if median of a weight > median.w. The default value is 1.5.
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
mu.phi	Prior-to-posterior sensitivity analysis of mu.phi. Default value is TRUE.
mu.phi.x.lim.low	Lower limit of the prior to posterior plot for mu.phi
mu.phi.x.lim.up	Upper limit of the prior to posterior plot for mu.phi
colour.hist.mu.phi	colour of the posterior mu.phi histogram
colour.prior.mu.phi	colour of the prior of mu.phi
colour.posterior.mu.phi	colour of the posterior of mu.phi
title.plot.mu.phi	Text for the title in the mu phi plot.
title.plot.weights	Text for the title of the posterior weights.
...	...

jarbes documentation built on June 28, 2025, 1:07 a.m.