Hi all,
I am trying to use the lmer() function in lme4 to model counts of capsules
on 786 plants (response variable with no zeros) spread across 23
populations with the explanatory variables size of plant (Area), time since
last burn of the population (TSB), and year (data collected across three
years. Obviously, there are correlations between time since burn (TSB) and
year, so a 2009 population that was burned in 2008 would be TSB = 1 and then
in 2010 it would be TSB=3. I tried treating year as a random factor
(1|Year), but I got the notorious "Cholmod" error.
My data set looks like this:
Site Site_IndNum Year TSB Num_Cap Area
1 PYBR002A PYBR002A_001 2008 3 18 463.34565
2 PYBR002A PYBR002A_002 2008 3 43 152.91702
3 PYBR002A PYBR002A_003 2008 3 25 80.11061
5 PYBR002A PYBR002A_005 2008 3 36 276.85285
6 PYBR002A PYBR002A_006 2008 3 39 1297.47777
7 PYBR002A PYBR002A_007 2008 3 23 992.42912
cap.lme1<-glmer(Num_Cap ~ as.factor(TSB) * Area * as.factor(Year) +
(1|Site),verbose=T,data=capprod,family=poisson,)
The above model receives the error message: In mer_finalize(ans) : false
convergence (8)
The output is:
0: 144803.19: 0.279342 0.100887 4.61433 0.373308 0.150254 0.000138755
0.000140513 4.48508e-05
1: 144803.19: 0.279342 0.100887 4.61433 0.373308 0.150254 0.000138755
0.000140513 4.48508e-05
However, when I try to remove the interaction terms, using
cap.lme2<-glmer(Num_Cap ~ as.factor(TSB) + Area + as.factor(Year) +
(1|Site),verbose=T,data=capprod,family=poisson,)
I get the message: "Error in asMethod(object) : matrix is not symmetric
[1,2]"
Any idea what this means and how to correct it? Needless to say, I am new
to mixed effects modeling and my data is unbalanced. The error seems to be
related to Area, which is a continuous variable. I don't get the
nonsymmetrical matrix error message. For example
cap.lme3<-glmer(Num_Cap ~ as.factor(TSB)*
as.factor(Year)+(1|Site)verbose=T,data=capprod,family=poisson,)
works fine.
I know that Area is an important variable, and so I don't want to remove it.
Thanks for any help.
Wade
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