tidy_identify_variables: Identify the variable corresponding to each model coefficient

In broom.helpers: Helpers for Model Coefficients Tibbles

Identify the variable corresponding to each model coefficient

Description

tidy_identify_variables() will add to the tidy tibble three additional columns: variable, var_class, var_type and var_nlevels.

Usage

tidy_identify_variables(x, model = tidy_get_model(x), quiet = FALSE)

Arguments

x	(data.frame) A tidy tibble as produced by ⁠tidy_*()⁠ functions.
model	(a model object, e.g. glm) The corresponding model, if not attached to x.
quiet	(logical) Whether broom.helpers should not return a message when requested output cannot be generated. Default is FALSE.

Details

It will also identify interaction terms and intercept(s).

var_type could be:

• "continuous",

• "dichotomous" (categorical variable with 2 levels),

• "categorical" (categorical variable with 3 levels or more),

• "intercept"

• "interaction"

• ⁠"ran_pars⁠ (random-effect parameters for mixed models)

• "ran_vals" (random-effect values for mixed models)

• "unknown" in the rare cases where tidy_identify_variables() will fail to identify the list of variables

For dichotomous and categorical variables, var_nlevels corresponds to the number of original levels in the corresponding variables.

For fixest models, a new column instrumental is added to indicate instrumental variables.

See Also

model_identify_variables()

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_attach_model(), tidy_disambiguate_terms(), tidy_group_by(), tidy_plus_plus(), tidy_remove_intercept(), tidy_select_variables()

Examples

df <- Titanic |>
  dplyr::as_tibble() |>
  dplyr::mutate(Survived = factor(Survived, c("No", "Yes")))
glm(
  Survived ~ Class + Age * Sex,
  data = df,
  weights = df$n,
  family = binomial
) |>
  tidy_and_attach() |>
  tidy_identify_variables()

lm(
  Sepal.Length ~ poly(Sepal.Width, 2) + Species,
  data = iris,
  contrasts = list(Species = contr.sum)
) |>
  tidy_and_attach(conf.int = TRUE) |>
  tidy_identify_variables()

broom.helpers documentation built on April 12, 2025, 2:26 a.m.