Add coefficients type and label as attributes
Source:R/tidy_add_coefficients_type.R
tidy_add_coefficients_type.RdAdd the type of coefficients ("generic", "logistic", "poisson",
"relative_risk" or "prop_hazard") and the corresponding coefficient labels,
as attributes to x (respectively
named coefficients_type and coefficients_label).
Usage
tidy_add_coefficients_type(
x,
exponentiate = attr(x, "exponentiate"),
model = tidy_get_model(x)
)Arguments
- x
(
data.frame)
A tidy tibble as produced bytidy_*()functions.- exponentiate
(
logical)
Whether or not to exponentiate the coefficient estimates. It should be consistent with the original call tobroom::tidy().- model
(a model object, e.g.
glm)
The corresponding model, if not attached tox.
See also
Other tidy_helpers:
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_term_labels(),
tidy_add_variable_labels(),
tidy_attach_model(),
tidy_disambiguate_terms(),
tidy_group_by(),
tidy_identify_variables(),
tidy_plus_plus(),
tidy_remove_intercept(),
tidy_select_variables()
Examples
ex1 <- lm(hp ~ mpg + factor(cyl), mtcars) |>
tidy_and_attach() |>
tidy_add_coefficients_type()
attr(ex1, "coefficients_type")
#> [1] "generic"
attr(ex1, "coefficients_label")
#> [1] "Beta"
df <- Titanic |>
dplyr::as_tibble() |>
dplyr::mutate(Survived = factor(Survived, c("No", "Yes")))
ex2 <- glm(
Survived ~ Class + Age * Sex,
data = df,
weights = df$n,
family = binomial
) |>
tidy_and_attach(exponentiate = TRUE) |>
tidy_add_coefficients_type()
attr(ex2, "coefficients_type")
#> [1] "logistic"
attr(ex2, "coefficients_label")
#> [1] "OR"