[R] Possible bug in lmer nested analysis with factors

[Yan Wong]

On 18 Sep 2005, at 16:27, Douglas Bates wrote:

> I have a couple of other comments.  You can write the nested grouping
> factors as Sundar did without having to explicitly evaluate the
> interaction term and drop unused levels.  The lmer function, like most
> modeling functions in R, uses the optional argument drop.unused.levels
> = TRUE when creating the model frame.

In other words, the use of "b:c" in a model formula, where both b and c
are factors, results in an internal call to evalq(b:c)[,drop=T] (or
equivalent), which is treated as a factor in a temporary model data
frame? I know little of the internals to R - that is new to me,
but does make sense for factors.

Thus I could use |a:b and |a:b:c as random terms in lme or lmer, even
though 'a' is a fixed, unnested factor.

Notation like this in the model formula does indeed aid clarity. By the
way, I noticed that in your mlmRev vignette you recommended this as good
practice for lea:school (page 3), but then omitted to do it on page 4.

> John Maindonald has already suggested the use of
>
>  (1|b/c) => (1|b:c) + (1|b)
>
> as "syntactic sugar" for the lmer formula and it is a reasonable
> request.

This is, indeed, the behaviour I was expecting.

> Unfortunately, implementing this is not high on my priority
> list at present. (We just made a massive change in the sparse matrix
> implementation in the Matrix package and shaking the bugs out of that
> will take a while.)

All your efforts in these areas are, I'm sure, much appreciated. I'm
certainly very interested in learning to use lmer, and welcome all the
improvements that are being made.

> In any case the general recommendation for nested grouping factors is
> first to ensure that they are stored as factors and then to create the
> sequence of interaction terms.

As a brief aside, I know that some people assume that lme treats random
effects as factors even if they are of a numeric type. It might be worth
doing a check in lmer (and even lme) that random effects are factors,
producing a warning if not. Again, this is a non-vital suggestion, and I
don't wish to take up any more of your time!

Thanks

Yan