pR2 {pscl} | R Documentation |
compute various pseduo-R2 measures for various GLMs
pR2(object, ...)
object |
a fitted model object, for now of class glm ,
polr , or mulitnom |
... |
additional arguments to be passed to or from functions |
Numerous pseudo r-squared measures have been proposed for generalized linear models, involving a comparison of the log-likelihood for the fitted model against the log-likelihood of a null/restricted model with no predictors, normalized to run from zero to one as the fitted model provides a better fit to the data (providing a rough analogue to the computation of r-squared in a linear regression).
A vector of length 6 containing
llh |
The log-likelihood from the fitted model |
llhNull |
The log-likelihood from the intercept-only restricted model |
G2 |
Minus two times the difference in the log-likelihoods |
McFadden |
McFadden's pseudo r-squared |
r2ML |
Maximum likelihood pseudo r-squared |
r2CU |
Cragg and Uhler's pseudo r-squared |
Simon Jackman jackman@stanford.edu
Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables. Sage. pp104-106.
data(admit) require(MASS) ## ordered probit model op1 <- polr(score ~ gre.quant + gre.verbal + ap + pt + female, Hess=TRUE, data=admit, method="probit") pR2(op1)