pscl (version 1.5.5)

pR2: compute various pseudo-R2 measures

Description

compute various pseudo-R2 measures for various GLMs

Usage

pR2(object, ...)

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

Arguments

object

a fitted model object for which logLik, update, and model.frame methods exist (e.g., an object of class glm, polr, or mulitnom)

...

additional arguments to be passed to or from functions

Author

Simon Jackman

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

data(admit)
## ordered probit model
op1 <- MASS::polr(score ~ gre.quant + gre.verbal + ap + pt + female,
            Hess=TRUE,
            data=admit,
            method="probit")
pR2(op1)