broom.helpers (version 1.19.0)

model_list_variables: List all the variables used in a model

Description

Including variables used only in an interaction.

Usage

model_list_variables(
  model,
  labels = NULL,
  only_variable = FALSE,
  add_var_type = FALSE,
  instrumental_suffix = " (instrumental)"
)
# S3 method for default
model_list_variables(
  model,
  labels = NULL,
  only_variable = FALSE,
  add_var_type = FALSE,
  instrumental_suffix = " (instrumental)"
)
# S3 method for lavaan
model_list_variables(
  model,
  labels = NULL,
  only_variable = FALSE,
  add_var_type = FALSE,
  instrumental_suffix = " (instrumental)"
)
# S3 method for logitr
model_list_variables(
  model,
  labels = NULL,
  only_variable = FALSE,
  add_var_type = FALSE,
  instrumental_suffix = " (instrumental)"
)

Value

A tibble with three columns:

• variable: the corresponding variable

• var_class: class of the variable (cf. stats::.MFclass())

• label_attr: variable label defined in the original data frame with the label attribute (cf. labelled::var_label())

• var_label: a variable label (by priority, labels if defined, label_attr if available, otherwise variable)

If add_var_type = TRUE:

• var_type: "continuous", "dichotomous" (categorical variable with 2 levels), "categorical" (categorical variable with 3 or more levels), "intercept" or "interaction"

• var_nlevels: number of original levels for categorical variables

Arguments

model

(a model object, e.g. glm)
A model object.

labels

(list or string)
An optional named list or named vector of custom variable labels.

only_variable

(logical)
If TRUE, will return only "variable" column.

add_var_type

(logical)
If TRUE, add var_nlevels and var_type columns.

instrumental_suffix

(string)
Suffix added to variable labels for instrumental variables (fixest models). NULL to add nothing.

See Also

Other model_helpers: model_compute_terms_contributions(), model_get_assign(), model_get_coefficients_type(), model_get_contrasts(), model_get_model(), model_get_model_frame(), model_get_model_matrix(), model_get_n(), model_get_nlevels(), model_get_offset(), model_get_pairwise_contrasts(), model_get_response(), model_get_response_variable(), model_get_terms(), model_get_weights(), model_get_xlevels(), model_identify_variables(), model_list_contrasts(), model_list_higher_order_variables(), model_list_terms_levels()

Examples

if (FALSE) { # interactive()
if (.assert_package("gtsummary", boolean = TRUE)) {
  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
  ) |>
  model_list_variables()

lm(
   Sepal.Length ~ poly(Sepal.Width, 2) + Species,
   data = iris,
   contrasts = list(Species = contr.sum)
  ) |>
  model_list_variables()

glm(
  response ~ poly(age, 3) + stage + grade * trt,
  na.omit(gtsummary::trial),
  family = binomial,
) |>
  model_list_variables()
}
}