pscl (version 1.5.2)

pR2: compute various pseudo-R2 measures

Description

compute various pseudo-R2 measures for various GLMs

Usage

pR2(object, ...)

Arguments

object

a fitted model object, for now of class glm, polr, or mulitnom

…

additional arguments to be passed to or from functions

Value

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

Details

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).

References

Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables. Sage. pp104-106.

See Also

extractAIC, logLik

Examples

# NOT RUN {
data(admit)
## ordered probit model
op1 <- MASS::polr(score ~ gre.quant + gre.verbal + ap + pt + female,
            Hess=TRUE,
            data=admit,
            method="probit")
pR2(op1)   
# }