Hi everyone,



(sorry if this has posted before, I’ve sent it twice but because I haven’t
received a copy or any replies it appears that it’s not getting onto the
list)



I’m using geeglm to do a resource function analysis on some dingo radio
collar data. When I try to fit the following  model R crashes and I get the
following error message (I’m actually running R through ESS, just in case
that’s relevant)

>  fit.geeglm <- geeglm(resp~rubbish, data=data, id=dogname,
family=binomial, corstr="exchangeable")



“This application has requested the Runtime to terminate it in an unusual
way.

Please contact the application's support team for more information.”



I’m also getting a Microsoft Windows pop up that says:

"R for Windows terminal front-end has stopped working"

A problem caused the program to stop working correctly.

Windows will close the program and notify you if a solution is available "





The weird thing is that if I reorder my data the model seems to fit OK. I
can reorder the data and run a model as follows:

>  sample <- data[sample(93948,93948),]  # (my data has 93948 rows)

> fit.geeglm
<-geeglm(resp~rubbish,data=sample,id=dogname,family=binomial,corstr="exchangeable")





My understanding of the corstr="exchangeable" correlation structure in
geeglm() is that it assumes equal correlation amongst all data points for
each dingo….so I can’t see why reordering the data changes anything….if I
was fitting something like an AR(1) model then I can see why reordering
changes things….



One reason I have considered is that geeglm() actually fits a correlation
structure for each *block *of* *id’s, rather than for all id’s?  For
example, if my data set had the following id structure id1, id1, id1, id2,
id2, id1, id1. Then it would fit 1 correlation structure to the first set of
id1’s and then a different correlation structure to the second set of id1’s?
Rather than fitting a single correlation structure to id1?



Does anyone have any suggestions on why this is happening??? And what I can
do to get the model to run?



My fall back model is to use glmer with random intercepts, but I really want
to use gee since it’s a marginal model and gives me robust SE’s.



Thanks for any ideas







The following is some more info that may be relevant:



For those unfamiliar with this type of resource function analysis it is
conceptually *similar* to a case control study. The “used” resource units
being the cases and coming from the radio collared telemetry data. The
“available” resource units are the controls and are randomly sampled from
the home range of each dingo (I have sampled 5 controls for each case). The
resource units are 40 by 40 m pixels from a GIS.



I have data for 4 dingos. It has 93948 rows and 9 variables. The first 1/6
of my data is the radio collar data “case” or “used resource units” (so
resp=1) and the next 5/6 of my data is the “control” or “available resource
units” (so resp =0).



And I u got this far thanks for your interest J



Chris Howden

Founding Partner

Tricky Solutions

Tricky Solutions 4 Tricky Problems

Evidence Based Strategic Development, IP Commercialisation and Innovation,
Data Analysis, Modelling, and Training

(mobile) 0410 689 945

(fax / office) (+618) 8952 7878

chris@trickysolutions.com.au

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