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Remove intercept(s)

Source: R/tidy_remove_intercept.R
tidy_remove_intercept.Rd

Will remove terms where var_type == "intercept".

Usage

tidy_remove_intercept(x, model = tidy_get_model(x))

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.

Details

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

See also

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_identify_variables(), tidy_plus_plus(), tidy_select_variables()

Examples

df <- Titanic |>
  dplyr::as_tibble() |>
  dplyr::mutate(Survived = factor(Survived))
glm(Survived ~ Class + Age + Sex, data = df, weights = df$n, family = binomial) |>
  tidy_and_attach() |>
  tidy_remove_intercept()
#> # A tibble: 5 × 11
#>   term      variable var_class var_type var_nlevels estimate std.error statistic
#>   <chr>     <chr>    <chr>     <chr>          <int>    <dbl>     <dbl>     <dbl>
#> 1 Class2nd  Class    character categor…           4   -1.02      0.196     -5.19
#> 2 Class3rd  Class    character categor…           4   -1.78      0.172    -10.4 
#> 3 ClassCrew Class    character categor…           4   -0.858     0.157     -5.45
#> 4 AgeChild  Age      character dichoto…           2    1.06      0.244      4.35
#> 5 SexMale   Sex      character dichoto…           2   -2.42      0.140    -17.2 
#> # ℹ 3 more variables: p.value <dbl>, conf.low <dbl>, conf.high <dbl>