Date: Wed, 6 Oct 1999 13:41:49 GMT
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
Organization: University of Missouri - St. Louis
Subject: Re: PROC MIXED 2
On 5 Oct 99 17:40:17 GMT, sarthur67@YAHOO.COM (Stephen Arthur) wrote:
: If I have one continuous outcome variable and 15 to 50
: discrete independent variables (each of which can be
: at four levels) and "several" other continuous
: What I want to do is find the simpliest model for
: these predictor variables. I am thinking I would need
: to use PROC GLM (which I have used) or PROC MIXED
: (which I have yet to use).
The simplest "model" of the outcome variable is it's mean. The next
simplest model would include one variable in a regression. No model
with 15 variables is simple. Does this answer your question?
Also, I don't see how PROC MIXED is appropriate for your data, one
should always look for more basic answers before going to the more
: Please don't flame me too hard on this one, I am just
: thinking (maybe not enough) about testing some ideas.
: Any thoughts? In general, can PC-SAS handle using
: these statistical procedures with 60+ variables and
: still remain functional?
SAS' computational limits aren't the issue. Regression and model
building are not black-box computer wizardry. You have to understand
something about statistics in general and regression in particular
As people often point out, your questions are similar to posting the
following in a medical newsgroup:
"I have really strange lump on my body. I want to remove the lump.
At my place of employment we have really sharp knives. Can anyone
provide me some insight into removing the lump?"