It didn't occur to me that the two renderered different results until you
mentioned it. But, here's what I have been able to detect.
lme.out$coef give the 'grand' intercept and the differences for each group from
that intercept (or other random effects). So, take the fixed effect for the
intercept (or other fixed effects) and then add the coef rendered from
lme.out$coef.
On the other hand,
coef(lme.out) gives the effects for all groups and all effects. So, the
difference is already computed.
If you have model with random intercepts and 1 fixed predictor. coef(lme.out)
will still provide a value for each group for the fixed predictor that doesn't
change. It's fixed. lme.out$coef doesn't replicate this fixed effect. It is
presented only once.
Again, I am not sure why this is the case. It just happens to be what I noticed
in a somewhat simple model.
HTH
Tom
-------------------------------------------------
Thomas D. Fletcher, PhD
Assistant Professor
Department of Psychology
University of Missouri - St. Louis
One University Boulevard
St. Louis, MO 63121
FletcherT@umsl.edu
Phone: (314) 516-5467
Fax: (314) 516-5392
www.umsl.edu/~fletchert
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________________________________
From: s-news-owner@lists.biostat.wustl.edu on behalf of Roberts, J. Kyle
Sent: Fri 7/21/2006 11:01 AM
To: s-news@lists.biostat.wustl.edu
Subject: [S] lme coefficients question
Dear All,
I have a question about lme. When I run:
coef(lme.out)
I get different results from when I run:
lme.out$coef
I know from my data that the coef(lme.out) contains the right values. Can
anyone tell me what lme.out$coef is doing?
***************************************
J. Kyle Roberts, Ph.D.
Baylor College of Medicine
Center for Educational Outreach
One Baylor Plaza, MS: BCM411
Houston, TX 77030-3411
713-798-6672 - 713-798-8201 Fax
jkrobert@bcm.edu
***************************************
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