[R-sig-ME] conditional AIC (cAIC) for lmer

John.Morrongiello at csiro.au John.Morrongiello at csiro.au
Wed May 7 03:38:45 CEST 2014

I would like to calculate the conditional AIC (cAIC) to compare a series of mixed models with different random effects structures for the purpose of ecological inference (method as per Vaida and Blanchard 2005 & Greven and Kneib 2010). I am using lme4 1.1-6 in R 3.1.0. Greven and Kneib provide a package for nlme; I got in touch with them directly and an lme4 version will likely be available later this year. I do, however, have a little bit more of a finite deadline and I was wondering if anyone else has developed a function to do this that works in the latest version of lme4? 

Kyle Edwards posted a function in 2008 (http://r.789695.n4.nabble.com/Using-Conditional-AIC-with-lmer-td847899.html) but this no longer works as the function 'hatTrace' is no longer available (http://r.789695.n4.nabble.com/Function-hatTrace-in-package-lme4-td4646071.html). In the package 'phmm' there is a 'cAIC' function but this doesn't work for lmer models.

Doing sequential likelihood ratio tests is another option, and I have seen some papers using DIC (which I thought was a Bayesian technique so not really applicable to a lmer model). I guess I could report AIC values and note that they are biased in this case due to issues around calculating degrees of freedom, but if there is a better option (e.g. cAIC) I'd prefer to go with that. 

Thanks for your time


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