
Calculate the R2 value for different model objects. Depending on the model, R2, pseudo-R2 or marginal / adjusted R2 values are returned.
r2(model, ...)
A statistical model.
Arguments passed down to the related r2-methods.
Returns a list containing values related to the most appropriate R2 for the given model. See the list below:
Logistic models: Tjur's R2
General linear models: Nagelkerke's R2
Multinomial Logit: McFadden's R2
Models with zero-inflation: R2 for zero-inflated models
Mixed models: Nakagawa's R2
Bayesian models: R2 bayes
r2_bayes
, r2_coxsnell
, r2_kullback
,
r2_loo
, r2_mcfadden
, r2_nagelkerke
,
r2_nakagawa
, r2_tjur
, r2_xu
and
r2_zeroinflated
.
# NOT RUN {
model <- glm(vs ~ wt + mpg, data = mtcars, family = "binomial")
r2(model)
if (require("lme4")) {
model <- lmer(Sepal.Length ~ Petal.Length + (1 | Species), data = iris)
r2(model)
}
# }
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