----- Original Message -----
*From:* Stella Karuri <mailto:swkaruri@insightful.com>
*To:* Splus listserve <mailto:s-news@lists.biostat.wustl.edu>
*Sent:* Wednesday, February 06, 2008 9:46 AM
*Subject:* Re: [S] Continuous covariates interpretation in glme
Splus does not standardize continous variates – by standardizing I
believe you mean centering to improve interpretability, (if x is the
continuous covariate, x*=(x-mean(x))).
When you specify the formula, you can center your covariate i.e.
instead of
glme( y~ x);
have
xst<- x-mean(x); glme(y~xst)
stella
* From: * s-news-owner@lists.biostat.wustl.edu
<mailto:s-news-owner@lists.biostat.wustl.edu>
[mailto:s-news-owner@lists.biostat.wustl.edu] *On Behalf Of *Ali &
Hind Lazrak
*Sent:* Tuesday, February 05, 2008 5:57 PM
*To:* Splus listserve
*Subject:* [S] Continuous covariates interpretation in glme
Dear all,
I ran a generalized mixed effects model to predict a binary outcome
using the 'glme' procedure. This model has two random subject
(persons nested within companies) and 5 fixed effects terms for the
subjects.
Among these 5 fixed effects variables, 2 are continuous.
As I am interpreting the results I have a question pertaining to the
treatment of continuous covariates:
Does Splus standardize automatically continuous covariates?
Thank you kindly for your answer.
Hind