lmer and SAS proc mixed

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