[R] R vs SAS and HLM on multilevel analysis- basic question

[Douglas Bates]

We may want to move this discussion to the R-SIG-Mixed-Models list,
which I have cc:'d on this reply.

On Sun, Jun 15, 2008 at 6:16 PM, eugen pircalabelu
<eugen_pircalabelu at yahoo.com> wrote:
> Hi R users!

> I am trying to learn some multilevel analysis, but unfortunately i am now very confused. The reason: http://www.ats.ucla.edu/stat/hlm/seminars/hlm_mlm/mlm_hlm_seminar.htm
> http://www.ats.ucla.edu/stat/sas/seminars/sas_mlm/mlm_sas_seminar.htm

> and
> MlmSoftRev. pdf from mlmRev package.

> >From what i see, the first two links seem to declare the level one variable as a random part (i don't know sas synthax, but i think i am right ) while Mr. Bates' pdf  says that a grouping variable is the random part of the model, though both models, use roughly the same type of information, some characteristic of the school, along with individual characteristics in explaining individual achivement.

I'm not exactly sure what you are asking.  If you are saying that the
terminology and notation can be confusing, I certainly agree.  I think
those who developed HLM and MLWin have done a tremendous service to
their users in providing them with sophisticated tools for modeling
data.  However, the way that they structure the model is really only
appropriate for models with nested random effects and, to my mind,
introduces many unnecessary and restrictive ways of thinking of the
data and the model.

> Am i mistaken somehow? If not, could they both be valid models (i presume) but each showing something else, in terms of connections between this variables?

As I said, I don't quite understand what you are asking and, rather
than formulate an answer to the wrong question, I'll ask if you can
rephrase your question and perhaps be more explicit about an example.
In particular, you made reference to a "school".  Are you referring to
a particular example?