get_title | R Documentation |
Get variable and value labels from ggeffects
-objects. predict_response()
saves information on variable names and value labels as additional attributes
in the returned data frame. This is especially helpful for labelled data
(see sjlabelled), since these labels can be used to set axis labels and
titles.
get_title(x, case = NULL)
get_x_title(x, case = NULL)
get_y_title(x, case = NULL)
get_legend_title(x, case = NULL)
get_legend_labels(x, case = NULL)
get_x_labels(x, case = NULL)
get_complete_df(x, case = NULL)
x |
An object of class |
case |
Desired target case. Labels will automatically converted into the
specified character case. See |
The titles or labels as character string, or NULL
, if variables
had no labels; get_complete_df()
returns the input list x
as single data frame, where the grouping variable indicates the
predicted values for each term.
library(ggeffects)
library(ggplot2)
data(efc, package = "ggeffects")
efc$c172code <- datawizard::to_factor(efc$c172code)
fit <- lm(barthtot ~ c12hour + neg_c_7 + c161sex + c172code, data = efc)
mydf <- predict_response(fit, terms = c("c12hour", "c161sex", "c172code"))
ggplot(mydf, aes(x = x, y = predicted, colour = group)) +
stat_smooth(method = "lm") +
facet_wrap(~facet, ncol = 2) +
labs(
x = get_x_title(mydf),
y = get_y_title(mydf),
colour = get_legend_title(mydf)
)
# adjusted predictions, a list of data frames (one data frame per term)
eff <- ggeffect(fit)
eff
get_complete_df(eff)
# adjusted predictions for education only, and get x-axis-labels
mydat <- eff[["c172code"]]
ggplot(mydat, aes(x = x, y = predicted, group = group)) +
stat_summary(fun = sum, geom = "line") +
scale_x_discrete(labels = get_x_labels(mydat))
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