Dear R-users,
I am using the most updated package of lme4 (lme4_0.999375-2). I have a
data set consisting of ~900 observations at ~440 independent survey
sites. There are an unbalanced number of surveys at each site. I am
attempting to develop several models evaluating the presence/absence of
a species (PRES) at these random sites (SITE) using a number of
predictor variables. The response variable (PRES) is binomial and the
included predictor variables are either proportions (e.g., AG, FOR,
OPEN, LDEV,or DEV) or numerical (COUNT[min. 1 to max. 37,mean = 10]).
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PROBLEM 1:
I have developed the following GLMM:
mix.1<-glmer(PRES~AG+FOR+OPEN+LDEV+DEV+COUNT+(1|SITE),family=binomial,data=merge1)
I receive the following error:
Warning message:
In mer_finalize(ans) : false convergence (8)
There is model output, but I am worried it might be biased.
I have tried:
-Data transformation of the predictor variables (e.g., log(COUNT)),
which does seem successful in some simpler models, but does not work
consistently.
-The most updated version of lme4
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PROBLEM #2:
In addition, I am interested in visualizing the predicted probabilities
from this output using the fixed effect function, but receive the
following message:
fixef(mix.1)
Error in UseMethod("fixef") : no applicable method for "fixef"
Any suggestions would be greatly appreciated!
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