Hi all,
I am fairly new to mixed effects models and lmer, so bear with me.
Here is a subset of my data, which includes a binary variable (lake (TOM or
JAN)), one other fixed factor (Age) and a random factor (Year).
lake FishID Age Increment Year
1 TOM 1 1 0.304 2007
2 TOM 1 2 0.148 2008
3 TOM 1 3 0.119 2009
4 TOM 1 4 0.053 2010
5 JAN 2 1 0.352 2009
6 JAN 2 2 0.118 2010
The model I'm trying to fit is:
m1 <- lmer(Increment ~ 0 + Age + Age*lake + (1|Year) + (1|Year:Age) +
(1|FishID),lakedata)
The error message I get is: *"Error in mer_finalize(ans) : Downdated X'X is
not positive definite, 27."*
*
*
>From reading up on the subject, I think my problem is that I can't
incorporate the 'lake' variable in a fixed-effect interaction because it is
only has one binary observation. But I don't know what to do to be able to
fit this model. Any help would be greatly appreciated!
-Sean
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