Message-ID: <1243371062.6357.7.camel@yod>
Date: 2009-05-26T20:51:03Z
From: Emmanuel Charpentier
Subject: lmer and SAS proc mixed
In-Reply-To: <329A68716B57D54E8D39FD3F8A4A84DF0EB942C0@um-mail0136.unimaas.nl>
Le mardi 26 mai 2009 ? 21:10 +0200, Viechtbauer Wolfgang (STAT) a
?crit :
> Try:
>
> proc mixed data=dt;
> class pid;
> model y= &fvars / solution outp=predicted;
> random intercept x1/sub=pid type=un solution;
> ods output SolutionF=fbeta;
> ods output SolutionR=rbeta;
>
> (note the addition of type=un on the line starting with random). I
> believe type=vc is the default, which does not allow the random
> intercept and slope to be correlated (which lmer does).
Can the parametrzation also play a role ?
In this case, I don't think : pid is the only "class" variable declared
in this proc step, which implies (or implied, in the times I was a SAS
user) that X1-...-X5 are continuous variables. Unless SAS started to
support a permanent class attribute in his datasets since v6.x (the last
I used with any kind of regularity)...
But I remember having been bitten by this when first trying to learn R
and hitting differences in regression/ANOVA coefficients. And, yes, the
dreaded "Type III SS" problem, which Bill Venables' "Exegeses on the
linear model" considerably enlightened.
Emmanuel Charpentier