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()
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