Forgive me if this answer is already somewhere on this site, but after extensive searching I have found nothing to help me. Here is a brief overview of the experiment:
- I have 18 tanks, each of which are split into 4 sections, each section has a different specie of wetland plant. Tank is my whole plot factor. Variety, or species (spp), is my split plot factor.
- I have 2 treatments, each at three levels. Nutrient addition (nut) and clipping (clip)
- I am measuring methane (ch4) emission as my response variable. I measured methane on 2 occasions, represented by variable t for time.
Data Structure
>str(ch4data)
'data.frame': 144 obs. of 6 variables:
$ tank: Factor w/ 18 levels "1","2","3","4",..: 1 1 1 1 2 2 2 2 3 3 ...
$ spp : Factor w/ 4 levels "Emac","Ewal",..: 4 2 3 1 3 4 1 2 1 4 ...
$ nut : Factor w/ 3 levels "1","2","3": 2 2 2 2 1 1 1 1 3 3 ...
$ clip: Factor w/ 3 levels "a","b","c": 3 3 3 3 2 2 2 2 2 2 ...
$ t: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...
$ ch4 : num 0.382 1.642 1.529 0.245 11.482 ...
Model
ch4.model=lme(fixed = ch4 ~ spp + nut + clip + t + spp*nut + spp*clip + spp*t +
nut*clip + nut*t + clip*t + spp*nut*clip + spp*nut*clip*t +
(nut*clip)%in%tank, random= ~1|tank, data=ch4data)
this gives the following error
Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at
level 0, block 1
Specifically, my questions are is: What is wrong with the fit of my model and what does this error mean? Additional help with fitting this model correctly would be much appreciated. I am new to R, so your response should take that into account.
