[R-sig-ME] [R] lme4 and false convergence

[ONKELINX, Thierry]

Dear Ben,

Your questions suite better in R-SIG-Mixed-Models which I am cc'ing.
Have checked the mailing list? Try RSiteSearch("lme4 false convergence")

HTH,

Thierry


------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Ben Zuckerberg
Verzonden: maandag 24 november 2008 18:37
Aan: r-help at r-project.org
Onderwerp: [R] lme4 and false convergence

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]). 
---------------------------------------------------------------------
PROBLEM 1:

I have developed the following GLMM:

mix.1<-glmer(PRES~AG+FOR+OPEN+LDEV+DEV+COUNT+(1|SITE),family=binomial,da
ta=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

---------------------------------------------------------------------
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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