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 <[EMAIL PROTECTED]> 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?
>>
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
-----
David Hewitt
Virginia Institute of Marine Science
http://www.vims.edu/fish/students/dhewitt/
--
View this message in context:
http://www.nabble.com/How-can-I-extract-the-AIC-score-from-a-mixed-model-object-produced-using-lmer--tp14406832p14419438.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
