Parallel slopes regression model
Description
geom_parallel_slopes() fits parallel slopes model and adds its line
output(s) to a ggplot object. Basically, it fits a unified model with
intercepts varying between groups (which should be supplied as standard
{ggplot2} grouping aesthetics: group, color, fill,
etc.). This function has the same nature as geom_smooth() from
{ggplot2} package, but provides functionality that geom_smooth()
currently doesn't have.
Usage
geom_parallel_slopes(
mapping = NULL,
data = NULL,
position = "identity",
...,
se = TRUE,
formula = y ~ x,
n = 100,
fullrange = FALSE,
level = 0.95,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
geom_parallel_slopes(
mapping = NULL,
data = NULL,
position = "identity",
...,
se = TRUE,
formula = y ~ x,
n = 100,
fullrange = FALSE,
level = 0.95,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE
)
Arguments
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)).
|
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 position argument 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 use position_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 layer()'s params argument. These
arguments broadly fall into one of 4 categories below. Notably, further
arguments to the position argument, or aesthetics that are required
can not be passed through .... Unknown arguments that are not part
of the 4 categories below are ignored.
-
Static aesthetics that are not mapped to a scale, but are at a fixed
value and apply to the layer as a whole. For example, colour = "red"
or linewidth = 3. The geom's documentation has an Aesthetics
section that lists the available options. The 'required' aesthetics
cannot be passed on to the params. Please note that while passing
unmapped aesthetics as vectors is technically possible, the order and
required length is not guaranteed to be parallel to the input data.
-
When constructing a layer using
a stat_*() function, the ... argument can be used to pass on
parameters to the geom part of the layer. An example of this is
stat_density(geom = "area", outline.type = "both"). The geom's
documentation lists which parameters it can accept.
-
Inversely, when constructing a layer using a
geom_*() function, the ... argument can be used to pass on parameters
to the stat part of the layer. An example of this is
geom_area(stat = "density", adjust = 0.5). The stat's documentation
lists which parameters it can accept.
-
The key_glyph argument of layer() may also be passed on through
.... This can be one of the functions described as
key glyphs, to change the display of the layer in the legend.
|
se |
Display confidence interval around model lines? TRUE by
default.
|
formula |
Formula to use per group in parallel slopes model. Basic
linear y ~ x by default.
|
n |
Number of points per group at which to evaluate model.
|
fullrange |
If TRUE, the smoothing line gets expanded to the range of the plot,
potentially beyond the data. This does not extend the line into any additional padding
created by expansion.
|
level |
Level of confidence interval to use (0.95 by default).
|
na.rm |
If FALSE, the default, missing values are removed with
a warning. If TRUE, missing values are silently removed.
|
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().
|
See Also
geom_categorical_model()
Examples
library(dplyr)
library(ggplot2)
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes(se = FALSE)
# Basic usage
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes()
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes(se = FALSE)
# Supply custom aesthetics
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes(se = FALSE, size = 4)
# Fit non-linear model
example_df <- house_prices %>%
slice(1:1000) %>%
mutate(
log10_price = log10(price),
log10_size = log10(sqft_living)
)
ggplot(example_df, aes(x = log10_size, y = log10_price, color = condition)) +
geom_point(alpha = 0.1) +
geom_parallel_slopes(formula = y ~ poly(x, 2))
# Different grouping
ggplot(example_df, aes(x = log10_size, y = log10_price)) +
geom_point(alpha = 0.1) +
geom_parallel_slopes(aes(fill = condition))
library(dplyr)
library(ggplot2)
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes(se = FALSE)
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes()
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes(se = FALSE)
ggplot(evals, aes(x = age, y = score, color = ethnicity)) +
geom_point() +
geom_parallel_slopes(se = FALSE, size = 4)
example_df <- house_prices %>%
slice(1:1000) %>%
mutate(
log10_price = log10(price),
log10_size = log10(sqft_living)
)
ggplot(example_df, aes(x = log10_size, y = log10_price, color = condition)) +
geom_point(alpha = 0.1) +
geom_parallel_slopes(formula = y ~ poly(x, 2))
ggplot(example_df, aes(x = log10_size, y = log10_price)) +
geom_point(alpha = 0.1) +
geom_parallel_slopes(aes(fill = condition))
, Chester Ismay [aut]