Coming from meta::forest()

If you already use meta::forest(), this vignette shows how ggmeta compares and how to reproduce familiar output.

library(ggmeta)
library(ggplot2)

The same object, a ggplot result

meta::forest() draws directly to a graphics device with a grid-based layout. ggmeta::ggforest() takes the same meta object but returns a ggplot:

library(meta)

m <- metabin(
  event.e = c(14, 30, 15, 22), n.e = c(100, 150, 100, 120),
  event.c = c(10, 25, 12, 18), n.c = c(100, 150, 100, 120),
  studlab = c("Study A", "Study B", "Study C", "Study D"),
  sm = "RR"
)

# meta::forest(m)   # base-graphics forest plot
ggforest(m)         # the same analysis, as a ggplot

The practical difference: everything after ggforest() is ggplot2. You compose with +, restyle with theme(), add annotations, and save with ggsave().

What maps to what

meta::forest() ggmeta
forest(m) ggforest(m)
col.square, col.diamond, … theme(), scale_*, layer aesthetics
rightcols (effect, CI, weight) ggforest(columns = TRUE)
custom leftcols / rightcols geom_forest_text() + format_effect()
xlim, xlab, smlab xlim(), labs(), or the xlab argument
layout = "JAMA" / "RevMan5" layout_jama(), layout_bmj(), layout_revman5()
prediction = TRUE drawn automatically when available
Study weights (square size) weight-proportional squares by default

Reproducing common tweaks

Relabel the axis and add a title. These are ordinary ggplot2 calls:

ggforest(m) +
  labs(title = "Risk of the event", x = "Risk ratio (log scale)")

Add the effect / CI / weight columns — the rightcols idea — with columns:

ggforest(m, columns = TRUE)

For a custom column (say a sample-size column of your own), reach for geom_forest_text(). tidy_meta() exposes the same tidy data frame ggforest() builds internally, so you can align your own text to the rows:

td <- tidy_meta(m)
studies <- td[!td$is_summary, ]
studies$effect_txt <- format_effect(studies$estimate, studies$ci_lower, studies$ci_upper)

ggforest(m) +
  geom_forest_text(aes(y = studlab, label = effect_txt), data = studies,
                   x = 4.2, hjust = 0) +
  expand_limits(x = 7)

When to use which