[R] random interactions in lme

[Jacob Michaelson]

On Apr 24, 2005, at 8:52 AM, Douglas Bates wrote:

> 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)
>
>
>

Thanks for the prompt reply.  I tried what you suggested, here's what I 
got:

 > turf.lme=lmer(dry_matter~compacting*variety+(1|rep)+(1|rc)+(1|rv), 
turf.data)
Error in lmer(dry_matter ~ compacting * variety + (1 | rep) + (1 | rc) 
+  :
	entry 3 in matrix[9,2] has row 3 and column 2

Just to see what the problem was, I deleted the third random term, and 
it didn't complain:

 > turf.lme=lmer(dry_matter~compacting*variety+(1|rep)+(1|rv), turf.data)
 > anova(turf.lme)
Analysis of Variance Table
                    Df Sum Sq Mean Sq  Denom F value    Pr(>F)
compacting          5 10.925   2.185 36.000  18.166  5.68e-09 ***
variety             2  2.518   1.259 36.000  10.468 0.0002610 ***
compacting:variety 10  6.042   0.604 36.000   5.023 0.0001461 ***

Now obviously this isn't a valid result since I need that third term; 
but interestingly, it didn't matter which term I deleted, so long as 
there were only two random terms.  Any ideas as to what the error 
message is referring to?

Thanks for the help,

Jake Michaelson