Add coefficients type and label as attributes
Source:R/tidy_add_coefficients_type.R
tidy_add_coefficients_type.Rd
Add 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_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"