tidy_add_estimate_to_reference_rows: Add an estimate value to references rows for categorical...

In broom.helpers: Helpers for Model Coefficients Tibbles

Add an estimate value to references rows for categorical variables

Description

For categorical variables with a treatment contrast (stats::contr.treatment()) or a SAS contrast (stats::contr.SAS()) will add an estimate equal to 0 (or 1 if exponentiate = TRUE) to the reference row.

Usage

tidy_add_estimate_to_reference_rows(
  x,
  exponentiate = attr(x, "exponentiate"),
  model = tidy_get_model(x),
  quiet = FALSE
)

Arguments

x	a tidy tibble
exponentiate	logical indicating whether or not to exponentiate the coefficient estimates. It should be consistent with the original call to broom::tidy()
model	the corresponding model, if not attached to x
quiet	logical argument whether broom.helpers should not return a message when requested output cannot be generated. Default is FALSE

Details

For categorical variables with a sum contrast (stats::contr.sum()), the estimate value of the reference row will be equal to the sum of all other coefficients multiplied by -1 (eventually exponentiated if exponentiate = TRUE), and obtained with emmeans::emmeans(). The emmeans package should therefore be installed. For sum contrasts, the model coefficient corresponds to the difference of each level with the grand mean.

For other variables, no change will be made.

If the reference_row column is not yet available in x, tidy_add_reference_rows() will be automatically applied.

See Also

Other tidy_helpers: tidy_add_coefficients_type(), tidy_add_contrasts(), 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

if (.assert_package("gtsummary", boolean = TRUE) && .assert_package("emmeans", boolean = TRUE)) {
df <- Titanic %>%
  dplyr::as_tibble() %>%
  dplyr::mutate(dplyr::across(where(is.character), factor))

df %>%
  glm(
    Survived ~ Class + Age + Sex,
    data = ., weights = .$n, family = binomial,
    contrasts = list(Age = contr.sum, Class = "contr.SAS")
  ) %>%
  tidy_and_attach(exponentiate = TRUE) %>%
  tidy_add_reference_rows() %>%
  tidy_add_estimate_to_reference_rows()

glm(
  response ~ stage + grade * trt,
  gtsummary::trial,
  family = binomial,
  contrasts = list(
    stage = contr.treatment(4, base = 3),
    grade = contr.treatment(3, base = 2),
    trt = contr.treatment(2, base = 2)
  )
) %>%
  tidy_and_attach() %>%
  tidy_add_reference_rows() %>%
  tidy_add_estimate_to_reference_rows()
}

broom.helpers documentation built on Feb. 16, 2023, 10:20 p.m.