baggr (version 0.7.8)

baggr_plot: Plotting method in baggr package

Description

Extracts study effects from the baggr model and plots them, possibly next to the hypereffect estimate.

Usage

baggr_plot(
  bg,
  hyper = FALSE,
  style = c("intervals", "areas", "forest_plot"),
  transform = NULL,
  prob = 0.5,
  prob_outer = 0.95,
  vline = TRUE,
  order = TRUE,
  values_outer = TRUE,
  values_size = 4,
  values_digits = 1,
  ...
)

Value

ggplot2 object

Arguments

bg

object of class baggr

hyper

logical; show hypereffect as the last row of the plot? alternatively you can pass colour for the hypermean row, e.g. hyper = "red"

style

"forest_plot" imitates the visual style of forest plots and also prints means and intervals next to each row; "intervals" (default) or "areas" use package bayesplot styles

transform

a function (e.g. exp(), log()) to apply to the values of group (and hyper, if hyper=TRUE) effects before plotting; when working with effects that are on log scale, exponent transform is used automatically, you can plot on log scale by setting transform = identity

prob

Probability mass for the inner interval in visualisation

prob_outer

Probability mass for the outer interval in visualisation

vline

logical; show vertical line through 0 in the plot?

order

logical; sort groups by magnitude of treatment effect?

values_outer

logical; use the interval corresponding to prob_outer when style = "forest_plot"? if not, the "inner" interval (prob) is used

values_size

size of the text values in the plot when style = "forest_plot"

values_digits

number of significant digits to use when style = "forest_plot"

...

extra arguments to pass to the bayesplot functions

Author

Witold Wiecek; the visual style is based on bayesplot package

See Also

bayesplot::MCMC-intervals for more information about bayesplot functionality; forest_plot for a typical meta-analysis alternative (which you can imitate using style = "forest_plot"); effect_plot for plotting treatment effects for a new group

Examples

fit <- baggr(schools, pooling = "none")
plot(fit, hyper = "red")
plot(fit, style = "areas", order = FALSE)
plot(fit, style = "forest_plot", order = FALSE)