[R-sig-ME] random factor and error messages in the model fitting

[Hank Stevens]

Hi Alex,
On Apr 2, 2008, at 10:17 AM, Alex Fajardo wrote:

> Dear r-sig-mixed-models webmail list members,
>
> I am new in the mixed-effects models world and I am learning from  
> Faraway's
> and Pinheiro & Bates' books and also from this list.
> I have 3, very straightforward, questions, but first a brief summary  
> of my
> analysis objectives. I am trying to analyze my data with mixed effects
> models where the fixed factor is represented by altitudinal  
> transects (4
> transects, where T4 is treeline, and T1, T2 and T3 are below  
> treeline). In
> each altitudinal transect I collected tissue samples from different
> age-class trees (a categorical variable with 4 levels, I, II, III,  
> and IV);
> all this with the main objective to compare specific leaf area -SLA-  
> of the
> treeline trees with lower elevation transects, and take into account  
> the
> age-class of the tree being considered. The data set is very  
> unbalanced and
> reading similar papers I concluded that age-class should be  
> considered a
> random factor nested in transects.
>
> *Question 1*: am I correct by considering age-class a random factor  
> nested
> within transect? If so, what should be the way to code the model?
> My suggestion is:
>> sla.termas = lmer(SLA ~ 1 + Transect + (1|Transect:Age),
> data=Treeline[Site=="TermasChillan",], na.action=na.omit) or
>> sla.termas = lmer(SLA ~ 1 + Transect + (Transect|Age),
> data=Treeline[Site=="TermasChillan",], na.action=na.omit), but I am  
> not
> sure.
I would assume that Age is NOT nested; if it is, you are saying that  
the effect of age could depend entirely on which transect you look at.  
Rather, I assume different ages simply have different responses, i.e.,  
(1|Age).

However, I would think that a fixed effect model is just as useful.
lm( SLA ~ Transect + Age + Age:Transect)

I am not sure why these altitudes or age class are considered a random  
draw from a large number of such classes that you know little about.  
They seem entirely repeated, and usefully so.

My two cents,
Hank
>
>
>
> In my learning process I followed examples given in Faraway's book  
> and just
> for learning purposes I computed my model in the way he does  
> (considering
> both factors random) and got, for some, variables the following  
> warning
> message:
>
>> sla.termas = lmer(SLA ~ 1 + (1|Transect) + (1|Transect:Age),
> data=Treeline[Site=="TermasChillan",], na.action=na.omit)
> *Warning message: In .local(x, ..., value) :
>  Estimated variance-covariance for factor 'Age' is singular*
>
> This is not good when I try to test the significance of the  
> variation among
> ages by ANOVA, since I get a Pr(>Chisq)=1; something must be wrong.  
> This
> situation happens with some variables and not with all of them:  
> strange?
>
> *Question 2*: any idea why this happens? What am I doing wrong?
>
> When I do get the model run (no such a warning message and just for  
> some
> other variables) and compare this model with a reduced version  
> (without the
> nested random factor, e.g., age-class) I run anova and get a p- 
> value. As
> suggested by Faraway I should also go for a p-value computing LRT  
> 1000 times
> (less conservative cf. Faraway) and most of the time I get the  
> following
> message:
>
>> lrstat = numeric(1000)
>> for(i in 1:1000){
> + rSLA = unlist(simulate(sla.termas2))
> + nmod =
> lmer(rSLA~1+(1| 
> Transect),data=Treeline[Site=="TermasChillan",],na.action=na.omit)
> + amod =
> lmer(rSLA~1+(1|Transect)+(1| 
> Transect:Age),data=Treeline[Site=="TermasChillan",],na.action=na.omit)
> + lrstat[i] = 2*(logLik(amod)-logLik(nmod))
> + }
> *Error in model.frame.default(data = Treeline[Site ==  
> "TermasChillan",  :
>  variable lengths differ (found for 'Transect')*
>
> *Question 3*: any idea why this happens? What am I doing wrong? I  
> made an
> artificial balanced data set to see whether the unbalanced situation  
> was the
> responsible for this message but it was not.
>
> I am new in the mixed-effects models world but I want to learn; your
> comments and advice will be greatly appreciated. Cheers,
>
>
>
> --
> Alex Fajardo, PhD
> Investigador Asociado
> Centro de Investigación en Ecosistemas de la Patagonia
> Bilbao 449. Coyhaique, CHILE
> Telefonos: 56-67-244503; (56) 8-4506354
> Fax: 56-67-244501
> alex.fajardo at ciep.cl
>
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>
> <ATT00001.txt>



Dr. Hank Stevens, Associate Professor
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