[R] Mixed Model notation SAS -> R

[Spencer Graves]

	  First, an almost trivial observation:  The model you specified for 
lme could more succinctly be specified as follows:

	  y ~ (a + b + c)^3

This expression implies the second and third order interactions.  It 
does NOT imply squared terms in case any two of "a", "b", or "c" are 
numeric.

	  To your question:  Do you get the same result when you omit the 
"correlation" argument?

	  * If yes, how can you further simplify the example to make it self 
contained, so someone else can actually see what you see and replicate 
the discrepancy that you see?

	  * If no, have you studied ch. 5 of Pinhiero and Bates, including 
working through the script file "ch05.R" included in 
"~\R-2.3.0\library\nlme\scripts" wherever you have R installed;  if you 
aren't using R 2.3.0 and nlme 3.1-72, please upgrade.

	  Also, PLEASE do read the posting guide! 
"www.R-project.org/posting-guide.html".  I very much appreciate you 
telling us you have Pinheiro and Bates.  If you could have also included 
a simple, self-contained example, I might have been able to provide a 
more useful reply with less effort than what I've expended in writing 
these few lines.

	  Ich hofe dass diese weinige Woerter koenen Sie hilfen.
	  Spencer Graves

Jörg Trojan wrote:
> Dear experts,
> 
> I'm trying to transfer a mixed model developed in SAS to R. This it what
> it looks like in SAS:
> 
> proc mixed method=ml;
>    class a b c subj;
>    model y = a|b|c;
>    repeated /subject=subj type=ar(1);
> 
> I tried something like this in R:
> 
> mixed <- lme(y ~ a + b + c + a*b + a*c + b*c + a*b*c,
>              random = ~ 1 | subj,
>              correlation = corAR1(form = ~ 1 | subj)
>              na.action = na.omit, method = "ML")
> 
> When I do an anova(mixed) the denomniator DFs do not compare to the ones
> SAS uses in calculating Type III results, In R a common, quite high
> (close to the total number of observations) denominator DF value is used
> for all effects, while SAS seems to calculate the DFs directly from  the
> number of class categories. So obviously I have to specify my random
> effects in R differently, but I don't know how...
> 
> Any hint on what I'm doing wrong is very much appreciated.
> 
> Thanks,
> Jörg
> 
> P.S. I have the Mixed Model book by Pinheiro and Bates here with me in
> case you can direct me to a specific section explaining my problem.
> 
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