[R-sig-ME] Fwd: lme() and SAS proc mixed
bbolker at gmail.com
Tue Oct 9 14:46:37 CEST 2012
[forwarding to r-sig-mixed-models . If you forget your password you
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-------- Original Message --------
Subject: lme() and SAS proc mixed
Resent-Date: Mon, 08 Oct 2012 12:16:53 -0400
Date: Mon, 8 Oct 2012 16:13:40 +0000
From: Verchinina, Lilia <lverchin at med.umich.edu>
To: bolker at mcmaster.ca <bolker at mcmaster.ca>
> Hello Ben,
> It seems you answered my question about translating proc mixed for
> linear mixed model into R lme(). Thanks a lot for you answer, it
> helped! I forgot my password with R-help, so I was not able to
> answer through R-help. When I use your code:
> random=~time|subject, data=...)
> I get estimates for both codes of Gender factor variable, while
> there is not thord reference level so I am not sure what is taken
> as a reference level for Gender.
I'm not sure which variable corresponds to Gender?
When you take out the intercept, there is no reference level
(i.e., zero is the reference value).
> I have the same problem with my SAS proc mix code:
> proc mixed data = survey method=reml; class subject var1 var3 var2
> time; model score = var2 score_base var4 var5 var3 var6 var7 var1
> time/ noint solution; random intercept timecontinious /
> subject=subject type=un g gcorr v vcorr;
> If I remove “-1” in the formula than you kindly provided, I do not
> get estimates for both Gender categories and one of the gender
> levels is used as a reference. I am curious what “-1” in the
> formula of your R code stands for? How can I fix this problem in
> SAS code, so I do not get estimates for both gender levels, but one
> of the two gender levels is used as a reference?
-1 is the same as "noint" in SAS-world, I believe. It specifies
that the model doesn't have an intercept. There is a section in
the Introduction to R on R's modeling syntax.
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