To evaluate the goodness of fit of the logistic regression model, calculating Nagelkerke's R squared from the result of glm(). The Nagelkerke's R squared means the power of explanation of the model.
NagelkerkeR2(rr)
The number of observations in which the model were fitted.
Nagelkerke's R squared.
The object with class "glm" and "lm", which would be generated by glm().
Minato Nakazawa minatonakazawa@gmail.com https://minato.sip21c.org/
Nagelkerke N (1991) A note on a general definition of the coefficient of determination. Biometrika, 78: 691-692.
Faraway JJ (2006) Extending the linear models with R: Generalized linear, mixed effects and nonparametric regression models. Chapman and Hall.
res <- glm(cbind(ncases,ncontrols) ~ agegp+alcgp+tobgp, data=esoph, family=binomial())
summary(res)
NagelkerkeR2(res)
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