[R-sig-ME] AIC and BIC with ML and REML

Gorjanc Gregor Gregor.Gorjanc at bfro.uni-lj.si
Tue Mar 31 00:30:24 CEST 2009

> In a way this question relates to the earlier discussion on whether to
> regard the random effects as parameters or as unobserved random
> variables.  The difference between -2 * l + 2 * p and -2 * l + 2 * (p
> + q) can be considered to be a question of how many parameters there
> are in the model.  In particular, do the random effects count as
> parameters?  I had an interesting discussion with Georges Monette
> about this a few days ago and both of us feel the saying the random
> effects don't affect the parameter count is underestimating the
> complexity of the model but saying they should add q to the number of
> parameters is overestimating the complexity.

Thanks for this comment. I will take this as a yes to: "Are there are several
definitions of AIC and BIC lurking around?".

DIC "solves" the issue of effective number of parameters to some extent
though it also has its own problems


> I don't know a good answer to the question of how to "count" the
> number of parameters in a mixed model (but I also don't feel that AIC
> or BIC should be taken too seriously - these quantities are, at best,
> a guide for model comparisons).



More information about the R-sig-mixed-models mailing list