- mapping
Set of aesthetic mappings created by aes(). If specified and
inherit.aes = TRUE (the default), it is combined with the default mapping
at the top level of the plot. You must supply mapping if 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 to ggplot().
A data.frame, or other object, will override the plot
data. All objects will be fortified to produce a data frame. See
fortify() for which variables will be created.
A function will be called with a single argument,
the plot data. The return value must be a data.frame, and
will be used as the layer data. A function can be created
from a formula (e.g. ~ head(.x, 10)).
- method
a character string indicating which method to be used for
pairwise comparisons. Default is "wilcox_test". Allowed methods
include pairwise comparisons methods implemented in the rstatix R
package. These methods are: "wilcox_test", "t_test", "sign_test",
"dunn_test", "emmeans_test", "tukey_hsd", "games_howell_test".
- method.args
a list of additional arguments used for the test method.
For example one might use method.args = list(alternative = "greater")
for wilcoxon test.
- ref.group
a character string or a numeric value specifying the
reference group. If specified, for a given grouping variable, each of the
group levels will be compared to the reference group (i.e. control group).
ref.group can be also "all". In this case, each of the
grouping variable levels is compared to all (i.e. basemean).
Allowed values can be:
numeric value: specifying
the rank of the reference group. For example, use ref.group = 1 when
the first group is the reference; use ref.group = 2 when the second
group is the reference, and so on. This works for all situations, including
i) when comparisons are performed between x-axis groups and ii) when
comparisons are performed between legend groups.
character
value: For example, you can use ref.group = "ctrl" instead of using
the numeric rank value of the "ctrl" group.
"all": In this
case, each of the grouping variable levels is compared to all (i.e.
basemean).
- label
character string specifying label. Can be:
the
column containing the label (e.g.: label = "p" or label =
"p.adj"), where p is the p-value. Other possible values are
"p.signif", "p.adj.signif", "p.format", "p.adj.format".
an
expression that can be formatted by the glue() package.
For example, when specifying label = "Wilcoxon, p = \{p\}", the
expression {p} will be replaced by its value.
a combination of
plotmath expressions and glue expressions. You may want some of the
statistical parameter in italic; for example:label = "Wilcoxon,
italic(p)= {p}"
.
- y.position
numeric vector with the y positions of the brackets
- group.by
(optional) character vector specifying the grouping variable;
it should be used only for grouped plots. Possible values are :
"x.var": Group by the x-axis variable and perform the test
between legend groups. In other words, the p-value is compute between legend
groups at each x position
"legend.var": Group by the legend
variable and perform the test between x-axis groups. In other words, the
test is performed between the x-groups for each legend level.
- dodge
dodge width for grouped ggplot/test. Default is 0.8. It's used to
dodge the brackets position when group.by = "legend.var".
- bracket.nudge.y
Vertical adjustment to nudge brackets by (in fraction
of the total height). Useful to move up or move down the bracket. If
positive value, brackets will be moved up; if negative value, brackets are
moved down.
- bracket.shorten
a small numeric value in [0-1] for shortening the width
of bracket.
- bracket.group.by
(optional); a variable name for grouping brackets
before adding step.increase. Useful for grouped plots. Possible values
include "x.var" and "legend.var".
- step.increase
numeric vector with the increase in fraction of total
height for every additional comparison to minimize overlap.
- tip.length
numeric vector with the fraction of total height that the
bar goes down to indicate the precise column/
- size
change the width of the lines of the bracket
- label.size
change the size of the label text
- family
change the font used for the text
- vjust
move the text up or down relative to the bracket.
- hjust
move the text left or right relative to the bracket.
- p.adjust.method
method for adjusting p values (see
p.adjust). Has impact only in a situation, where
multiple pairwise tests are performed; or when there are multiple grouping
variables. Ignored when the specified method is "tukey_hsd" or
"games_howell_test" because they come with internal p adjustment
method. Allowed values include "holm", "hochberg", "hommel", "bonferroni",
"BH", "BY", "fdr", "none". If you don't want to adjust the p value (not
recommended), use p.adjust.method = "none".
- p.adjust.by
possible value is one of c("group", "panel").
Default is "group": for a grouped data, if pairwise test is
performed, then the p-values are adjusted for each group level
independently. P-values are adjusted by panel when p.adjust.by =
"panel".
- symnum.args
a list of arguments to pass to the function
symnum for symbolic number coding of p-values. For
example, symnum.args <- list(cutpoints = c(0, 0.0001, 0.001, 0.01,
0.05, Inf), symbols = c("****", "***", "**", "*", "ns")).
In other words, we use the following convention for symbols indicating
statistical significance:
ns: p > 0.05
*: p <= 0.05
**: p <= 0.01
***: p <= 0.001
****: p <= 0.0001
- hide.ns
can be logical value (TRUE or FALSE) or a character vector ("p.adj" or "p").
- remove.bracket
logical, if TRUE, brackets are removed from the
plot.
Case when logical value. If TRUE, hide ns symbol when
displaying significance levels. Filter is done by checking the column
p.adj.signif, p.signif, p.adj and p.
Case
when character value. Possible values are "p" or "p.adj", for filtering out
non significant.
- position
Position adjustment, either as a string naming the adjustment
(e.g. "jitter" to use position_jitter), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.
- na.rm
If FALSE (the default), removes missing values with a
warning. If TRUE silently removes missing values.
- show.legend
logical. Should this layer be included in the legends?
NA, the default, includes if any aesthetics are mapped.
FALSE never includes, and TRUE always includes.
It can also be a named logical vector to finely select the aesthetics to
display.
- inherit.aes
If FALSE, overrides the default aesthetics,
rather than combining with them. This is most useful for helper functions
that define both data and aesthetics and shouldn't inherit behaviour from
the default plot specification, e.g. borders().
- parse
logical for parsing plotmath expression.
- ...
other arguments passed on to layer. These are often
aesthetics, used to set an aesthetic to a fixed value, like color =
"red" or size = 3. They may also be parameters to the paired
geom/stat.
- stat
The statistical transformation to use on the data for this
layer, either as a ggproto Geom subclass or as a string naming the
stat stripped of the stat_ prefix (e.g. "count" rather than
"stat_count")
- stack
logical value. Default is FALSE; should be set to TRUE for
stacked bar plots or line plots. If TRUE, then the brackets are
automatically removed and the dodge value is set to zero.