Indicate the type of coefficient among "generic", "logistic", "poisson", "relative_risk" or "prop_hazard".
Usage
model_get_coefficients_type(model)
# Default S3 method
model_get_coefficients_type(model)
# S3 method for class 'glm'
model_get_coefficients_type(model)
# S3 method for class 'negbin'
model_get_coefficients_type(model)
# S3 method for class 'geeglm'
model_get_coefficients_type(model)
# S3 method for class 'fixest'
model_get_coefficients_type(model)
# S3 method for class 'biglm'
model_get_coefficients_type(model)
# S3 method for class 'glmerMod'
model_get_coefficients_type(model)
# S3 method for class 'clogit'
model_get_coefficients_type(model)
# S3 method for class 'polr'
model_get_coefficients_type(model)
# S3 method for class 'multinom'
model_get_coefficients_type(model)
# S3 method for class 'svyolr'
model_get_coefficients_type(model)
# S3 method for class 'clm'
model_get_coefficients_type(model)
# S3 method for class 'clmm'
model_get_coefficients_type(model)
# S3 method for class 'coxph'
model_get_coefficients_type(model)
# S3 method for class 'crr'
model_get_coefficients_type(model)
# S3 method for class 'tidycrr'
model_get_coefficients_type(model)
# S3 method for class 'cch'
model_get_coefficients_type(model)
# S3 method for class 'model_fit'
model_get_coefficients_type(model)
# S3 method for class 'LORgee'
model_get_coefficients_type(model)
See also
Other model_helpers:
model_compute_terms_contributions()
,
model_get_assign()
,
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()
,
model_list_variables()
Examples
lm(hp ~ mpg + factor(cyl), mtcars) |>
model_get_coefficients_type()
#> [1] "generic"
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_get_coefficients_type()
#> [1] "logistic"