Get the number of observations
For binomial and multinomial logistic models, will also return the number of events.
model_get_n(model) ## Default S3 method: model_get_n(model) ## S3 method for class 'glm' model_get_n(model) ## S3 method for class 'gam' model_get_n(model) ## S3 method for class 'glmerMod' model_get_n(model) ## S3 method for class 'multinom' model_get_n(model) ## S3 method for class 'coxph' model_get_n(model) ## S3 method for class 'survreg' model_get_n(model)
model |
a model object |
For Poisson models, will return the number of events and exposure time
(defined with stats::offset()).
For Cox models (survival::coxph()), will return the number of events and
exposure time.
See tidy_add_n() for more details.
The total number of observations (N_obs), of events (N_event) and of
exposure time (Exposure) are stored as attributes of the returned tibble.
This function does not cover lavaan models (NULL is returned).
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_offset(),
model_get_response(),
model_get_terms(),
model_get_weights(),
model_get_xlevels(),
model_identify_variables(),
model_list_contrasts(),
model_list_terms_levels(),
model_list_variables()
lm(hp ~ mpg + factor(cyl) + disp:hp, mtcars) %>%
model_get_n()
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_n()
mod <- glm(
Survived ~ Class * Age + Sex, data = Titanic %>% as.data.frame(),
weights = Freq, family = binomial
)
mod %>% model_get_n()
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)
mod %>% model_get_n()
mod <- glm(response ~ age + grade * trt, gtsummary::trial, family = poisson)
mod %>% model_get_n()
mod <- glm(
response ~ trt * grade + offset(ttdeath),
gtsummary::trial,
family = poisson
)
mod %>% model_get_n()
df <- survival::lung %>% dplyr::mutate(sex = factor(sex))
mod <- survival::coxph(survival::Surv(time, status) ~ ph.ecog + age + sex, data = df)
mod %>% model_get_n()
mod <- lme4::lmer(Reaction ~ Days + (Days | Subject), lme4::sleepstudy)
mod %>% model_get_n()
mod <- lme4::glmer(response ~ trt * grade + (1 | stage),
family = binomial, data = gtsummary::trial
)
mod %>% model_get_n()
mod <- lme4::glmer(cbind(incidence, size - incidence) ~ period + (1 | herd),
family = binomial, data = lme4::cbpp
)
mod %>% model_get_n()Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.