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Re: Continuous covariates interpretation in glme

To: "Splus listserve" <s-news@lists.biostat.wustl.edu>
Subject: Re: Continuous covariates interpretation in glme
From: "Stella Karuri" <swkaruri@insightful.com>
Date: Wed, 6 Feb 2008 09:46:22 -0800
In-reply-to: <001301c86863$9c0603b0$6601a8c0@Alazrak>
References: <001301c86863$9c0603b0$6601a8c0@Alazrak>
Thread-index: AchoY7J3WkLLFS8HQq+IALLs5t+1fwAf4RyQ
Thread-topic: [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] 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

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