geom_forest_text() places a column of text labels aligned with the study
rows of a forest plot — for example event counts, sample sizes, weights, or
the effect estimate rendered as text. Rows align automatically through the
shared y (study) aesthetic; the horizontal position of the column is set
with the x argument. Place a column beside the data by widening the panel
with ggplot2::expand_limits().
Usage
geom_forest_text(
mapping = NULL,
data = NULL,
stat = "identity",
position = "identity",
...,
x = NULL,
hjust = 0,
size = 3.2,
na.rm = TRUE,
show.legend = FALSE,
inherit.aes = FALSE
)Arguments
- mapping
Set of aesthetic mappings created by
aes(). If specified andinherit.aes = TRUE(the default), it is combined with the default mapping at the top level of the plot. You must supplymappingif there is no plot mapping.- data
The data to be displayed in this layer. There are three options:
If
NULL, the default, the data is inherited from the plot data as specified in the call toggplot().A
data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. Seefortify()for which variables will be created.A
functionwill be called with a single argument, the plot data. The return value must be adata.frame, and will be used as the layer data. Afunctioncan be created from aformula(e.g.~ head(.x, 10)).- stat
The statistical transformation to use on the data for this layer. When using a
geom_*()function to construct a layer, thestatargument can be used to override the default coupling between geoms and stats. Thestatargument accepts the following:A
Statggproto subclass, for exampleStatCount.A string naming the stat. To give the stat as a string, strip the function name of the
stat_prefix. For example, to usestat_count(), give the stat as"count".For more information and other ways to specify the stat, see the layer stat documentation.
- position
A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The
positionargument accepts the following:The result of calling a position function, such as
position_jitter(). This method allows for passing extra arguments to the position.A string naming the position adjustment. To give the position as a string, strip the function name of the
position_prefix. For example, to useposition_jitter(), give the position as"jitter".For more information and other ways to specify the position, see the layer position documentation.
- ...
Other arguments passed on to
ggplot2::layer(), often used to set an aesthetic to a fixed value, e.g.colour = "grey30"orfontface = "bold".- x
Fixed horizontal position for the column, in x-axis data units. If
NULL,xmust be supplied throughmapping.- hjust
Horizontal justification. Default
0(left-aligned), so a column reads cleanly from itsxposition rightward.- size
Text size in millimetres. Default
3.2.- na.rm
If
TRUE(default), missing labels are dropped silently.- show.legend
logical. Should this layer be included in the legends?
NA, the default, includes if any aesthetics are mapped.FALSEnever includes, andTRUEalways includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, useTRUE. IfNA, all levels are shown in legend, but unobserved levels are omitted.- inherit.aes
If
FALSE(default) the layer does not inherit the forest plot'sx/xmin/xmax/weightmapping, so onlyyandlabelneed to be supplied.
Aesthetics
geom_forest_text() understands the following aesthetics
(required aesthetics are in bold):
y— row position (map to the same study variable as the forest layers)label— text to displaycolour— text colour (default: "black")size— text size; set via thesizeargumentfontface,family,angle,alpha
Examples
library(ggplot2)
df <- data.frame(
study = c("A", "B", "C"),
estimate = c(0.5, 0.8, 0.3),
lower = c(0.2, 0.6, 0.1),
upper = c(0.8, 1.0, 0.5),
n = c(120, 240, 90)
)
ggplot(df, aes(y = study, x = estimate, xmin = lower, xmax = upper)) +
geom_forest_ci() +
geom_forest_text(aes(y = study, label = n), x = 1.15) +
expand_limits(x = 1.25)
