View source: R/model_identify_variables.R
model_identify_variables | R Documentation |
It will also identify interaction terms and intercept(s).
model_identify_variables(model)
## Default S3 method:
model_identify_variables(model)
## S3 method for class 'lavaan'
model_identify_variables(model)
## S3 method for class 'aov'
model_identify_variables(model)
## S3 method for class 'clm'
model_identify_variables(model)
## S3 method for class 'clmm'
model_identify_variables(model)
## S3 method for class 'gam'
model_identify_variables(model)
## S3 method for class 'model_fit'
model_identify_variables(model)
## S3 method for class 'logitr'
model_identify_variables(model)
model |
(a model object, e.g. |
A tibble with four columns:
term
: coefficients of the model
variable
: the corresponding variable
var_class
: class of the variable (cf. stats::.MFclass()
)
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
tidy_identify_variables()
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_list_contrasts()
,
model_list_higher_order_variables()
,
model_list_terms_levels()
,
model_list_variables()
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_identify_variables()
lm(
Sepal.Length ~ poly(Sepal.Width, 2) + Species,
data = iris,
contrasts = list(Species = contr.sum)
) |>
model_identify_variables()
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