# lme4: Why is AIC no longer displayed when using REML [duplicate]

I have a simple question, understanding the basic usage of the lme4 package. I am following the tutorial by Bodo Winter (http://www.bodowinter.com/tutorial/bw_LME_tutorial.pdf).

In this tutorial, Bodo calculates a random effects model using the two commands:

 library(lme4)
politeness.model = lmer(frequency ~ attitude + (1|subject) + (1|scenario),
data=politeness)
summary(politeness.model)


However, his printout of the output includes the AIC and BIC values (page 8), which are not included in the current version of lme4 (1.1.7). Do you have any idea why this is the case? Although, one can compute the two values using the maximum likelyhood algorithm (by using the REML=False option), I am confused why they are no longer included in the default output.

• For what it's worth, AIC(politeness.model) and BIC(politeness.model) appear to work ... (at least in the development version of lme4) – Ben Bolker Jan 5 '15 at 15:04
Although lme4 follows a fairly standard R convention of reporting the AIC, BIC, etc. in summary, I actually think this is mostly useless anyway, since the AIC/BIC for a single model basically doesn't contain any information. You can use it to compare across models, but that's easier to do with anova(model1,model2) or AIC(model1,model2) (or bbmle::AICtab(model1,model2), which gives a more useful summary).