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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.
Currently not used.
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.
r2_bayes
r2_coxsnell
r2_kullback
r2_loo
r2_mcfadden
r2_nagelkerke
r2_nakagawa
r2_tjur
r2_xu
r2_zeroinflated
# NOT RUN { model <- glm(vs ~ wt + mpg, data = mtcars, family = "binomial") r2(model) library(lme4) model <- lmer(Sepal.Length ~ Petal.Length + (1 | Species), data = iris) r2(model) # }
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