R help - Jun 2010 - How to code mixed model with nested factors in lmer

Hi,

 

I have coding question on mixed model in R. I am using R2.11.0 in
windows. I have an experiment with 2 fixed effect factors - A and B. The
levels of B are within the levels of A factor. The model is very similar
to a split plot design except the nesting relationship between the 2
fixed effect factors. For example: there are 2 levels for A - GM and ZM.
There are 7 levels of B in total (G1-G4 and Z1 - Z3) - but G1, G2, G3,
G4 only appear in GM while Z1, Z2 and Z3 only appear in ZM. The SAS code
is like the following:

Proc Mixed data = a;

Class A B rep;

Model y = A B(A);

Random rep rep*A;

Run;

 

I tried to code this model in R using lmer(). It turned out that R has
some issues with nesting levels with fixed effect. I changed and tried a
few models just for diagnostic purpose. And I found whenever I included
the nesting fixed effects, I got the following error message: "Problem
in .C("mixed_EM",: Singularity in backsolve, while calling subroutine
mixed_EM". I am wondering whether someone can help me set up this mixed
model in R. 

Thanks 

 

Huiyan Zhao

 


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