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

From: Douglas Bates <bates_at_stat.wisc.edu>
Date: Mon, 16 Jun 2008 08:22:52 -0500

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?



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