tidy_add_term_labels {broom.helpers} | R Documentation |
Add term labels
Description
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 |
a tidy tibble |
labels |
an optional named list or named vector of custom term labels |
interaction_sep |
separator for interaction terms |
categorical_terms_pattern |
a glue pattern for
labels of categorical terms with treatment or sum contrasts
(see examples and |
model |
the corresponding model, if not attached to |
quiet |
logical argument whether broom.helpers should not return
a message when requested output cannot be generated. Default is |
strict |
logical argument whether broom.helpers should return an error
when requested output cannot be generated. Default is |
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
df <- Titanic %>%
dplyr::as_tibble() %>%
dplyr::mutate(Survived = factor(Survived, c("No", "Yes"))) %>%
labelled::set_variable_labels(
Class = "Passenger's class",
Sex = "Sex"
)
mod <- df %>%
glm(Survived ~ Class * Age * Sex, data = ., weights = .$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}"
)