plot | R Documentation |
A generic plot-method for ggeffects
-objects.
## S3 method for class 'ggeffects'
plot(
x,
show_ci = TRUE,
ci_style = c("ribbon", "errorbar", "dash", "dot"),
show_data = FALSE,
show_residuals = FALSE,
show_residuals_line = FALSE,
data_labels = FALSE,
limit_range = FALSE,
collapse_group = FALSE,
show_legend = TRUE,
show_title = TRUE,
show_x_title = TRUE,
show_y_title = TRUE,
case = NULL,
colors = NULL,
alpha = 0.15,
dot_alpha = 0.35,
jitter = NULL,
dodge = 0.25,
dot_size = NULL,
line_size = NULL,
use_theme = TRUE,
log_y = FALSE,
connect_lines = FALSE,
facets,
grid,
one_plot = TRUE,
verbose = TRUE,
ci = show_ci,
ci.style = ci_style,
rawdata = show_data,
add.data = show_data,
residuals = show_residuals,
residuals.line = show_residuals_line,
label.data = data_labels,
limit.range = limit_range,
collapse.group = collapse_group,
dot.alpha = dot_alpha,
dot.size = dot_size,
line.size = line_size,
connect.lines = connect_lines,
show.title = show_title,
show.x.title = show_x_title,
show.y.title = show_y_title,
use.theme = use_theme,
show.legend = show_legend,
one.plot = one_plot,
log.y = log_y,
...
)
theme_ggeffects(base_size = 11, base_family = "")
show_pals()
x |
An object of class |
show_ci |
Logical, if |
ci_style |
Character vector, indicating the style of the confidence
bands. May be either |
show_data |
Logical, if |
show_residuals |
Logical, if |
show_residuals_line |
Logical, if |
data_labels |
Logical, if |
limit_range |
Logical, if |
collapse_group |
For mixed effects models, name of the grouping variable
of random effects. If |
show_legend |
Logical, shows or hides the plot legend. |
show_title |
Logical, shows or hides the plot title- |
show_x_title |
Logical, shows or hides the plot title for the x-axis. |
show_y_title |
Logical, shows or hides the plot title for the y-axis. |
case |
Desired target case. Labels will automatically converted into the
specified character case. See |
colors |
Character vector with color values in hex-format, valid
color value names (see Following options are valid for
|
alpha |
Alpha value for the confidence bands. |
dot_alpha |
Alpha value for data points, when |
jitter |
Numeric, between 0 and 1. If not |
dodge |
Value for offsetting or shifting error bars, to avoid overlapping.
Only applies, if a factor is plotted at the x-axis (in such cases, the
confidence bands are replaced by error bars automatically), or if
|
dot_size |
Numeric, size of the point geoms. |
line_size |
Numeric, size of the line geoms. |
use_theme |
Logical, if |
log_y |
Logical, if |
connect_lines |
Logical, if |
facets, grid |
Logical, defaults to |
one_plot |
Logical, if |
verbose |
Logical, toggle warnings and messages. |
ci, add.data, rawdata, residuals, residuals.line, label.data, limit.range, collapse.group, dot.alpha, dot.size, line.size, connect.lines, show.title, show.x.title, show.y.title, use.theme, one.plot, ci.style, show.legend, log.y |
Deprecated
arguments. Use |
... |
Further arguments passed down to |
base_size |
Base font size. |
base_family |
Base font family. |
For proportional odds logistic regression (see ?MASS::polr
)
or cumulative link models in general, plots are automatically facetted
by response.level
, which indicates the grouping of predictions based on
the level of the model's response.
A ggplot2-object.
For generalized linear models (glms), residualized scores are
computed as inv.link(link(Y) + r)
where Y
are the predicted
values on the response scale, and r
are the working residuals.
For (generalized) linear mixed models, the random effect are also
partialled out.
Load library(ggplot2)
and use theme_set(theme_ggeffects())
to set
the ggeffects-theme as default plotting theme. You can then use further
plot-modifiers, e.g. from sjPlot, like legend_style()
or font_size()
without losing the theme-modifications.
There are pre-defined colour palettes in this package. Use show_pals()
to show all available colour palettes.
library(sjlabelled)
data(efc)
efc$c172code <- as_label(efc$c172code)
fit <- lm(barthtot ~ c12hour + neg_c_7 + c161sex + c172code, data = efc)
dat <- ggpredict(fit, terms = "c12hour")
plot(dat)
# facet by group, use pre-defined color palette
dat <- ggpredict(fit, terms = c("c12hour", "c172code"))
plot(dat, facet = TRUE, colors = "hero")
# don't use facets, b/w figure, w/o confidence bands
dat <- ggpredict(fit, terms = c("c12hour", "c172code"))
plot(dat, colors = "bw", show_ci = FALSE)
# factor at x axis, plot exact data points and error bars
dat <- ggpredict(fit, terms = c("c172code", "c161sex"))
plot(dat)
# for three variables, automatic facetting
dat <- ggpredict(fit, terms = c("c12hour", "c172code", "c161sex"))
plot(dat)
# show all color palettes
show_pals()
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