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Get variable and value labels from ggeffects
-objects. Functions like
ggpredict()
or ggeffect()
save 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)
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.
An object of class ggeffects
, as returned by any ggeffects-function;
for get_complete_df()
, must be a list of ggeffects
-objects.
Desired target case. Labels will automatically converted into the
specified character case. See ?sjlabelled::convert_case
for more details
on this argument.
if (require("sjmisc", quietly = TRUE) &&
require("ggplot2", quietly = TRUE) &&
require("effects", quietly = TRUE)) {
data(efc)
efc$c172code <- to_factor(efc$c172code)
fit <- lm(barthtot ~ c12hour + neg_c_7 + c161sex + c172code, data = efc)
mydf <- ggpredict(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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