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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