R help - Jan 2013 - Error in mer_finalize(ans) : Downdated X'X is not positive definite, 8.

Dear All,
I have conducted an experiment in order to examine predation pressure in the
surroundings of potential wildlife road-crossing structures.  I have
documented predation occurrence (binary?) in these structures and calculated
several possible explanatory variables describing the spatial heterogeneity
in several scales.  At the landscape scale I have calculated the percentage
of different land-uses (7) in buffers around the structures with changing
radii (100m, 250m, 500m, 1000m and 2000m).  For each radii I have generated
a set of all possible models from the given 7 variables related to this
radii.    
I have tried to account for random effects. A spatial random effect ? the
structure itself as a repeated measurement, by adding the term
(1|Road_Structure).  A temporal random effect ? the observation session (is
it correct to say that this examines possible learning in time ?), by adding
the term (1|Session.ord).   
I have generated 4 sets for each radii: 1) with both random effects, 2+3)
only one (each) random effect, and 4) none.    
I have tried to model the relationships using glm, glmer and lmer.
The problem is that in the full model (all 7 variables) of some sets with
random effects I get the following error:
*Error in mer_finalize(ans) : Downdated X'X is not positive definite, 8.*

The only record of this error I have found in the internet is for data with
missing observation.  This doesn't comply with my data set.  I think it
might be a singularity problem but I don't know how to check it, and as a
result, I obviously don't know how to fix it.
I have attached example R scripts (for the radius 2000) and the data table.
Any help is highly appreciated !
Thanks and all the best,
-- 
Yoav Avneon
Department of Life Sciences 
The Spatial Ecology Lab
Ben Gurion University of the Negev
P.O.B. 653   Beer-Sheva 84105 
ISRAEL

+972-52-3391918 (mobile)
+972-8-6461350 (lab)
-------------------------------------------------------------------------------------------------------------------------------------------
Yoav Yeled Teva

ANP_multi_landscape_No_RE_Buffer_2000m.R
<http://r.789695.n4.nabble.com/file/n4656015/ANP_multi_landscape_No_RE_Buffer_2000m.R>
ANP_multi_landscape_Plus_RE_Str_Session_Buffer_2000m.R
<http://r.789695.n4.nabble.com/file/n4656015/ANP_multi_landscape_Plus_RE_Str_Session_Buffer_2000m.R>
ANP_multi_landscape_Plus_RE_Str_Buffer_2000m.R
<http://r.789695.n4.nabble.com/file/n4656015/ANP_multi_landscape_Plus_RE_Str_Buffer_2000m.R>
ANP_multi_landscape_Plus_RE_Session_Buffer_2000m.R
<http://r.789695.n4.nabble.com/file/n4656015/ANP_multi_landscape_Plus_RE_Session_Buffer_2000m.R>
Raw_data_4_logit_reg_Only_str_point_all_Landscape_vars.txt
<http://r.789695.n4.nabble.com/file/n4656015/Raw_data_4_logit_reg_Only_str_point_all_Landscape_vars.txt>



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Yoav Avneon <Avneony <at> bgu.ac.il> writes:
> I have conducted an experiment in order to examine predation pressure in
the
> surroundings of potential wildlife road-crossing structures.  I have
> documented predation occurrence (binary?) in these structures and
calculated
> several possible explanatory variables describing the spatial heterogeneity
> in several scales.  At the landscape scale I have calculated the percentage
> of different land-uses (7) in buffers around the structures with changing
> radii (100m, 250m, 500m, 1000m and 2000m).  For each radii I have generated
> a set of all possible models from the given 7 variables related to this
> radii.    
> I have tried to account for random effects. A spatial random effect ? the
> structure itself as a repeated measurement, by adding the term
> (1|Road_Structure).  A temporal random effect ? the observation session (is
> it correct to say that this examines possible learning in time ?), by
adding
> the term (1|Session.ord).   
> I have generated 4 sets for each radii: 1) with both random effects, 2+3)
> only one (each) random effect, and 4) none.    
> I have tried to model the relationships using glm, glmer and lmer.
> The problem is that in the full model (all 7 variables) of some sets with
> random effects I get the following error:
> *Error in mer_finalize(ans) : Downdated X'X is not positive definite,
8.*
> 
> The only record of this error I have found in the internet is for data with
> missing observation.  This doesn't comply with my data set.  I think it
> might be a singularity problem but I don't know how to check it, and as
a
> result, I obviously don't know how to fix it.
> I have attached example R scripts (for the radius 2000) and the data table.
> Any help is highly appreciated !
> Thanks and all the best,
  Questions like this (and follow-ups) should probably go to
r-sig-mixed-models at r-project.org.

  I don't have time to dig into this in detail, but I would start
by (1) centering and scaling all of your variables (see ?scale, and
Schielzeth 2010 _Methods in Ecology and Evolution_ and (2) checking
the correlations among your variables; if they are strongly correlated
you have lots of options (none of them perfect), much discussed on
the internet, including discarding some variables or using PCA.