convergence error code in mixed effects models
On Dec 13, 2007 4:15 PM, Ilona Leyer <ileyer at yahoo.de> wrote:
Dear All, I want to analyse treatment effects with time series data: I measured e.g. leaf number (five replicate plants) in relation to two soil pH - after 2,4,6,8 weeks. I used mixed effects models, but some analyses didn?t work. It seems for me as if this is a randomly occurring problem since sometimes the same model works sometimes not. An example:
names(test)
[1] "rep" "treat" "leaf" "week"
library (lattice) library (nlme) test<-groupedData(leaf~week|rep,outer=~treat,test) model<-lme(leaf~treat,random=~leaf|rep)
Error in lme.formula(leaf~ treat, random = ~week|rep)
Really!? You gave lme a model with random = ~ leaf | rep (and no data specification) and it tried to fit a model with random = ~ week | rep? Are you sure that is an exact transcript?
:
nlminb problem, convergence error code = 1;
message = iteration limit reached without convergence
(9)
Has anybody an idea to solve this problem?
Oh, I have lots of ideas but without a reproducible example I can't hope to decide what might be the problem. It appears that the model may be over-parameterized. Assuming that there are 4 different values of week then ~ week | rep requires fitting 10 variance-covariance parameters. That's a lot. The error code indicates that the optimizer is taking