How can I extract the AIC score from a mixed model object produced using lmer?
David Barron-3 wrote:
You can calculate the AIC as follows: (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) aic1 <- AIC(logLik(fm1))
Is AIC() [extractAIC()] "valid" for models with random effects? I noticed that the help page for extractAIC() does not list models with random effects. I think this boils down to the difference between the likelihoods for models with and without random effects, and I don't know. Just curious...
On 12/18/07, Peter H Singleton <psingleton at fs.fed.us> wrote:
I am running a series of candidate mixed models using lmer (package lme4) and I'd like to be able to compile a list of the AIC scores for those models so that I can quickly summarize and rank the models by AIC. When I do logistic regression, I can easily generate this kind of list by creating the model objects using glm, and doing:
md <- c("md1.lr", "md2.lr", "md3.lr")
aic <- c(md1.lr$aic, md2.lr$aic, md3.lr$aic)
aic2 <- cbind(md, aic)
but when I try to extract the AIC score from the model object produced by lmer I get:
md1.lme$aic
NULL Warning message: In md1.lme$aic : $ operator not defined for this S4 class, returning NULL So... How do I query the AIC value out of a mixed model object created by lmer?
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