plot_forest: Forest Plot for Meta-Analysis

In metaBMA: Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Forest Plot for Meta-Analysis

Description

Plots estimated effect sizes for all studies.

Usage

plot_forest(
  meta,
  from,
  to,
  shrinked = "random",
  summary = c("mean", "hpd"),
  mar = c(4.5, 12, 4, 0.3),
  cex.axis = 1,
  ...
)

Arguments

meta	fitted meta-analysis model
from	lower limit of the x-axis
to	upper limit of the x-axis
shrinked	which meta-analysis model should be used to show (shrinked) estimates of the study effect sizes. The name must match the corresponding name in the list meta. Can be suppressed by shrinked = ""
summary	character vector with two values: first, either "mean" or "50%"; and second, either highest-probability-density interval "hpd" or the Bayesian credibility interval "bci".
mar	margin of the plot in the order c(bottom, left, top, right) (see par)
cex.axis	size of the y-axis annotation for the labels of studies.
...	arguments passed to plot (e.g., from, to)

See Also

meta_bma, meta_fixed, meta_random

Examples

data(towels)
mf <- meta_fixed(logOR, SE, study, towels)
plot_forest(mf, mar = c(4.5, 20, 4, .2), xlab = "Log Odds Ratio")

metaBMA documentation built on Sept. 13, 2023, 9:06 a.m.