To facilitate the use of broom helpers with pipe, it is recommended to
attach the original model as an attribute to the tibble of model terms
generated by broom::tidy().
tidy_attach_model(x, model, .attributes = NULL)tidy_and_attach(
model,
tidy_fun = tidy_with_broom_or_parameters,
conf.int = TRUE,
conf.level = 0.95,
exponentiate = FALSE,
model_matrix_attr = TRUE,
...
)
tidy_get_model(x)
tidy_detach_model(x)
(data.frame)
A tidy tibble as produced by tidy_*() functions.
(a model object, e.g. glm)
A model to be attached/tidied.
(list)
Named list of additional attributes to be attached to x.
(function)
Option to specify a custom tidier function.
(logical)
Should confidence intervals be computed? (see broom::tidy())
(numeric)
Level of confidence for confidence intervals (default: 95%).
(logical)
Whether or not to exponentiate the coefficient estimates.
This is typical for logistic, Poisson and Cox models,
but a bad idea if there is no log or logit link; defaults to FALSE.
(logical)
Whether model frame and model matrix should be added as attributes of
model (respectively named "model_frame" and "model_matrix") and
passed through
Other arguments passed to tidy_fun().
tidy_attach_model() attach the model to a tibble already generated while
tidy_and_attach() will apply broom::tidy() and attach the model.
Use tidy_get_model() to get the model attached to the tibble and
tidy_detach_model() to remove the attribute containing the model.
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_term_labels(),
tidy_add_variable_labels(),
tidy_disambiguate_terms(),
tidy_identify_variables(),
tidy_plus_plus(),
tidy_remove_intercept(),
tidy_select_variables()
mod <- lm(Sepal.Length ~ Sepal.Width + Species, data = iris)
tt <- mod |>
tidy_and_attach(conf.int = TRUE)
tt
tidy_get_model(tt)
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