COUNT (version 1.3.2)

modelfit: Fit Statistics for generalized linear models

Description

modelfit is used following a glm() or glm.nb() model to produce a list of model fit statistics.

Usage

modelfit(x)

Arguments

x

the only argument is the name of the fitted glm or glm.nb function model

Value

• obs
  number of model observatiions
• aic
  AIC statistic
• xvars
  number of model predictors
• rdof
  residial degrees of freedom
• aic_n
  AIC, 'aic'/'obs'
• ll
  log-likelihood
• bic_r
  BIC - Raftery parameterization
• bic_l
  BIC - log-likelihood Standard definition (Stata)
• bic_qh
  Hannan-Quinn IC statistic (Limdep)

Details

modelfit is to be used as a post-estimation function, following the use of glm() or glm.nb().

References

Hilbe, J.M. (2011), Negative Binomial Regression, second edition, Cambridge University Press.

Hilbe, J.M. (2009), Logistic Regression Models, Chapman Hall/CRC

See Also

glm, glm.nb

Examples

## Hilbe (2011), Table 9.17
library(MASS)
data(lbwgrp)
nb9_3 <- glm.nb(lowbw ~ smoke + race2 + race3 + offset(log(cases)), data=lbwgrp)
summary(nb9_3)
exp(coef(nb9_3))
modelfit(nb9_3)