model_get_response {broom.helpers}

Get model response

Description

This function does not cover lavaan models (NULL is returned).

Usage

model_get_response(model)

## Default S3 method:
model_get_response(model)

## S3 method for class 'glm'
model_get_response(model)

## S3 method for class 'glmerMod'
model_get_response(model)

## S3 method for class 'model_fit'
model_get_response(model)

Arguments

model

a model object

See Also

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_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) + disp:hp, mtcars) %>%
  model_get_response()

mod <- glm(
  response ~ stage * grade + trt,
  gtsummary::trial,
  family = binomial,
  contrasts = list(stage = contr.sum, grade = contr.treatment(3, 2), trt = "contr.SAS")
)
mod %>% model_get_response()

mod <- glm(
  Survived ~ Class * Age + Sex,
  data = Titanic %>% as.data.frame(),
  weights = Freq,
  family = binomial
)
mod %>% model_get_response()

d <- dplyr::as_tibble(Titanic) %>%
  dplyr::group_by(Class, Sex, Age) %>%
  dplyr::summarise(
    n_survived = sum(n * (Survived == "Yes")),
    n_dead = sum(n * (Survived == "No"))
  )
mod <- glm(cbind(n_survived, n_dead) ~ Class * Age + Sex, data = d, family = binomial, y = FALSE)
mod %>% model_get_response()