Conditional Akaike information criterion for lme4

Share:

Description

Provides functions for the estimation of the conditional Akaike information in generalized mixed-effects models fitted with (g)lmer form lme4.

Details

Package: cAIC
Type: Package
Version: 0.2
Date: 2014-05-23
License: GPL (>=2)

Author(s)

Benjamin Saefken, David Ruegamer, Thomas Kneib and Sonja Greven.

Maintainer: Benjamin Saefken <bsaefke@uni-goettingen.de>

References

Saefken, B., Kneib T., van Waveren C.-S. and Greven, S. (2014) A unifying approach to the estimation of the conditional Akaike information in generalized linear mixed models. Electronic Journal Statistics Vol. 8, 201-225.

Greven, S. and Kneib T. (2010) On the behaviour of marginal and conditional AIC in linear mixed models. Biometrika 97(4), 773-789.

Efron , B. (2004) The estimation of prediction error. J. Amer. Statist. Ass. 99(467), 619-632.

Examples

1
2
3
b <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)

cAIC(b)