Select variables to keep/drop
Will remove unselected variables from the results.
To remove the intercept, use tidy_remove_intercept().
tidy_select_variables(x, include = everything(), model = tidy_get_model(x))
x |
a tidy tibble |
include |
variables to include. Accepts tidyselect
syntax. Use |
model |
the corresponding model, if not attached to |
If the variable column is not yet available in x,
tidy_identify_variables() will be automatically applied.
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_reference_rows(),
tidy_add_term_labels(),
tidy_add_variable_labels(),
tidy_attach_model(),
tidy_disambiguate_terms(),
tidy_identify_variables(),
tidy_plus_plus(),
tidy_remove_intercept()
res <- Titanic %>%
dplyr::as_tibble() %>%
dplyr::mutate(Survived = factor(Survived)) %>%
glm(Survived ~ Class + Age * Sex, data = ., weights = .$n, family = binomial) %>%
tidy_and_attach() %>%
tidy_identify_variables()
res
res %>% tidy_select_variables()
res %>% tidy_select_variables(include = "Class")
res %>% tidy_select_variables(include = -c("Age", "Sex"))
res %>% tidy_select_variables(include = starts_with("A"))
res %>% tidy_select_variables(include = all_categorical())
res %>% tidy_select_variables(include = all_dichotomous())
res %>% tidy_select_variables(include = all_interaction())
res %>% tidy_select_variables(
include = c("Age", all_categorical(dichotomous = FALSE), all_interaction())
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