pscl (version 1.02)

pR2: compute various pseduo-R2 measures

Description

compute various pseduo-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

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)