R help - Apr 2005 - random interactions in lme

Hi All,

I'm taking an Experimental Design course this semester, and have spent 
many long hours trying to coax the professor's SAS examples into 
something that will work in R (I'd prefer that the things I learn not 
be tied to a license).  It's been a long semester in that regard.

One thing that has really frustrated me is that lme has an extremely 
counterintuitive way for specifying random terms.  I can usually figure 
out how to express a single random term, but if there are multiple 
terms or random interactions, the documentation available just doesn't 
hold up.

Here's an example: a split block (strip plot) design evaluated in SAS 
with PROC MIXED (an excerpt of the model and random statements):

model DryMatter = Compacting|Variety / outp = residuals ddfm = 
satterthwaite;
random Rep Rep*Compacting Rep*Variety;

Now the fixed part of that model is easy enough in lme: 
"DryMatter~Compacting*Variety"
But I can't find anything that adequately explains how to simply add 
the random terms to the model, ie "rep + rep:compacting +
rep:variety";
anything to do with random terms in lme seems to go off about grouping 
factors, which just isn't intuitive for me.

Any help?

Thanks in advance!

--Jake Michaelson

Jacob Michaelson wrote:
> Hi All,
> 
> I'm taking an Experimental Design course this semester, and have spent 
> many long hours trying to coax the professor's SAS examples into 
> something that will work in R (I'd prefer that the things I learn not
be
> tied to a license).  It's been a long semester in that regard.
> 
> One thing that has really frustrated me is that lme has an extremely 
> counterintuitive way for specifying random terms.  I can usually figure 
> out how to express a single random term, but if there are multiple terms 
> or random interactions, the documentation available just doesn't hold
up.
> 
> Here's an example: a split block (strip plot) design evaluated in SAS 
> with PROC MIXED (an excerpt of the model and random statements):
> 
> model DryMatter = Compacting|Variety / outp = residuals ddfm = 
> satterthwaite;
> random Rep Rep*Compacting Rep*Variety;
> 
> Now the fixed part of that model is easy enough in lme: 
> "DryMatter~Compacting*Variety"
> But I can't find anything that adequately explains how to simply add
the
> random terms to the model, ie "rep + rep:compacting +
rep:variety";
> anything to do with random terms in lme seems to go off about grouping 
> factors, which just isn't intuitive for me.
The grouping factor is rep because the random effects are associated 
with the levels of rep.

I don't always understand the SAS notation so you may need to help me 
out here.  Do you expect to get a single variance component estimate for 
Rep*Compacting and a single variance component for Rep*Variety?  If so, 
you would specify the model in lmer by first creating factors for the 
interaction of Rep and Compacting and the interaction of Rep and Variety.

dat$RepC <- with(dat, Rep:Compacting)[drop=TRUE]
dat$RepV <- with(dat, Rep:Variety)[drop=TRUE]
fm <- lmer(DryMatter ~ Compacting*Variety+(1|Rep)+(1|RepC)+(1|RepV), dat)