List levels of categorical terms
Only for categorical variables with treatment, SAS or sum contrasts, and categorical variables with no contrast.
model_list_terms_levels(
model,
label_pattern = "{level}",
variable_labels = NULL
)
## Default S3 method:
model_list_terms_levels(
model,
label_pattern = "{level}",
variable_labels = NULL
)model |
a model object |
label_pattern |
a glue pattern for term labels (see examples) |
variable_labels |
an optional named list or named vector of
custom variable labels passed to |
A tibble with ten columns:
variable: variable
contrasts_type: type of contrasts ("sum" or "treatment")
term: term name
level: term level
level_rank: rank of the level
reference: logical indicating which term is the reference level
reference_level: level of the reference term
var_label: variable label obtained with model_list_variables()
var_nlevels: number of levels in this variable
dichotomous: logical indicating if the variable is dichotomous
label: term label (by default equal to term level)
The first nine columns can be used in label_pattern.
Other model_helpers:
model_compute_terms_contributions(),
model_get_assign(),
model_get_coefficients_type(),
model_get_contrasts(),
model_get_model_frame(),
model_get_model_matrix(),
model_get_model(),
model_get_nlevels(),
model_get_n(),
model_get_offset(),
model_get_response(),
model_get_terms(),
model_get_weights(),
model_get_xlevels(),
model_identify_variables(),
model_list_contrasts(),
model_list_variables()
glm(
am ~ mpg + factor(cyl),
data = mtcars,
family = binomial,
contrasts = list(`factor(cyl)` = contr.sum)
) %>%
model_list_terms_levels()
df <- Titanic %>%
dplyr::as_tibble() %>%
dplyr::mutate(Survived = factor(Survived, c("No", "Yes")))
mod <- df %>%
glm(
Survived ~ Class + Age + Sex,
data = ., weights = .$n, family = binomial,
contrasts = list(Age = contr.sum, Class = "contr.helmert")
)
mod %>% model_list_terms_levels()
mod %>% model_list_terms_levels("{level} vs {reference_level}")
mod %>% model_list_terms_levels("{variable} [{level} - {reference_level}]")
mod %>% model_list_terms_levels(
"{ifelse(reference, level, paste(level, '-', reference_level))}"
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