repolr (version 2.0)

QIC: Quasilikelihood Information Criterion

Description

The quasilikelihood information criterion (QIC) developed by Pan (2001) is a modification of the Akaike information criterion (AIC) for models fit by GEE.

Usage

QIC(x)

Arguments

x

is a fitted model using grepolr

Value

• The quasilikelihood for the fitted model.

References

Pan, W. (2001). Akaikes information criterion in generalized estimating equations. Biometrics, 57, 120-125.

Examples

## linear polynomial
data(QoL)
space <- 1:10
mod1 <- grepolr(QoL~factor(Time)+factor(Treat),subjects="Patient",
         data=QoL, categories=10, times=c(1,2,3),poly=1,space=space)
## cubic polynomial
mod3 <- grepolr(QoL~factor(Time)+factor(Treat),subjects="Patient",
         data=QoL, categories=10, times=c(1,2,3),poly=3,space=space)
QIC(mod1)
QIC(mod3)