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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