forest_plot function

Forest Plot

Creates a forest plot for gMAP analysis objects.

forest_plot(
  x,
  prob = 0.95,
  est = c("both", "MAP", "Mean", "none"),
  model = c("stratified", "both", "meta"),
  point_est = c("median", "mean"),
  size = 1.25,
  alpha = 0.5
)

Arguments

• x: gMAP object.

• prob: confidence interval width and probability mass of credible intervals.

• est: can be set to one of both (default), MAP, Mean or none. Controls which model estimates are to be included.

• model: controls which estimates are displayed per study. Either stratified (default), both or meta.

• point_est: shown point estimate. Either median (default) or mean.

• size: controls point and linesize.

• alpha: transparency of reference line. Setting alpha=0

  suppresses the reference line.

Returns

The function returns a ggplot2 plot object.

Details

The function creates a forest plot suitable for gMAP analyses. Note that the Meta-Analytic-Predictive prior is included by default in the plot as opposed to only showing the estimated model mean. See the examples below to obtain standard forest plots.

Also note that the plot internally flips the x and y-axis. Therefore, if you want to manipulate the x-axis, you have to give commands affecting the y-axis (see examples).

Customizing ggplot2 plots

The returned plot is a ggplot2 object. Please refer to the "Customizing Plots" vignette which is part of RBesT

documentation for an introduction. For simple modifications (change labels, add reference lines, ...) consider the commands found in bayesplot-helpers. For more advanced customizations please use the ggplot2 package directly. A description of the most common tasks can be found in the R Cookbook and a full reference of available commands can be found at the c("ggplot2 documentation\n", "site").

Examples

# we consider the example AS MAP analysis
example(AS)

# default forest plot for a gMAP analysis
forest_plot(map_AS)

# standard forest plot (only stratified estimate and Mean)
forest_plot(map_AS, est = c("Mean"), model = "stratified")

# to further customize these plots, first load bayesplot and ggplot2
library(bayesplot)
library(ggplot2)

# to make plots with red colors, big fonts for presentations, suppress
# the x axis label and add another title (with a subtitle)
color_scheme_set("red")
theme_set(theme_default(base_size = 16))
forest_plot(map_AS, size = 2) +
  yaxis_title(FALSE) +
  ggtitle("Ankylosing Spondylitis Forest Plot",
    subtitle = "Control Group Response Rate"
  )

# the defaults are set with
color_scheme_set("blue")
theme_set(theme_default(base_size = 12))

See Also

gMAP