Will add term labels in a label
column, based on:
labels provided in
labels
argument if provided;factor levels for categorical variables coded with treatment, SAS or sum contrasts (the label could be customized with
categorical_terms_pattern
argument);variable labels when there is only one term per variable;
term name otherwise.
Usage
tidy_add_term_labels(
x,
labels = NULL,
interaction_sep = " * ",
categorical_terms_pattern = "{level}",
model = tidy_get_model(x),
quiet = FALSE,
strict = FALSE
)
Arguments
- x
(
data.frame
)
A tidy tibble as produced bytidy_*()
functions.- labels
(
list
orstring
)
An optional named list or named vector of custom term labels.- interaction_sep
(
string
)
Separator for interaction terms.- categorical_terms_pattern
(
glue pattern
)
A glue pattern for labels of categorical terms with treatment or sum contrasts (see examples andmodel_list_terms_levels()
).- model
(a model object, e.g.
glm
)
The corresponding model, if not attached tox
.- quiet
(
logical
)
Whetherbroom.helpers
should not return a message when requested output cannot be generated. Default isFALSE
.- strict
(
logical
)
Whetherbroom.helpers
should return an error when requested output cannot be generated. Default isFALSE
.
Details
If the variable_label
column is not yet available in x
,
tidy_add_variable_labels()
will be automatically applied.
If the contrasts
column is not yet available in x
,
tidy_add_contrasts()
will be automatically applied.
It is possible to pass a custom label for any term in labels
,
including interaction terms.
See also
Other tidy_helpers:
tidy_add_coefficients_type()
,
tidy_add_contrasts()
,
tidy_add_estimate_to_reference_rows()
,
tidy_add_header_rows()
,
tidy_add_n()
,
tidy_add_pairwise_contrasts()
,
tidy_add_reference_rows()
,
tidy_add_variable_labels()
,
tidy_attach_model()
,
tidy_disambiguate_terms()
,
tidy_identify_variables()
,
tidy_plus_plus()
,
tidy_remove_intercept()
,
tidy_select_variables()
Examples
if (FALSE) { # interactive()
df <- Titanic |>
dplyr::as_tibble() |>
dplyr::mutate(Survived = factor(Survived, c("No", "Yes"))) |>
labelled::set_variable_labels(
Class = "Passenger's class",
Sex = "Sex"
)
mod <-
glm(Survived ~ Class * Age * Sex, data = df, weights = df$n, family = binomial)
mod |>
tidy_and_attach() |>
tidy_add_term_labels()
mod |>
tidy_and_attach() |>
tidy_add_term_labels(
interaction_sep = " x ",
categorical_terms_pattern = "{level} / {reference_level}"
)
}