[R-sig-ME] Unbalanced presence/absence data
Andrew J Tyre
atyre2 at unlnotes.unl.edu
Tue Feb 3 15:41:32 CET 2009
Hi Anna,
if your covariates are at the site level, then I suggest reducing your
sample to a pure binomial case - counts of individuals with and without
parasites. This is exactly the case when you will run into large amounts
of overdispersion, because between individual differences in
susceptibility and exposure within sites lead to larger than binomial
variation between sites. However, you can at least partially account for
this by including a random effect of site in the model - this leads to the
"normal-binomial" model discussed in earlier posts (how do you all find
those earlier posts?).
hth,
Drew Tyre
School of Natural Resources
University of Nebraska-Lincoln
416 Hardin Hall, East Campus
3310 Holdrege Street
Lincoln, NE 68583-0974
phone: +1 402 472 4054
fax: +1 402 472 2946
email: atyre2 at unl.edu
http://snr.unl.edu/tyre
"Renwick, A. R." <a.renwick at abdn.ac.uk>
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02/03/2009 08:33 AM
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Subject
[R-sig-ME] Unbalanced presence/absence data
I am trying to analyse some data I have on the presence/absence of
parasite infestation on small mammals using a GLMM, however I have a
severely unbalanced data set in that I have a large number of 0's compared
to 1's (i.e. 1333 0's and 86 1's).
The response variable (presence/absence) is at the individual level
whereas all the explanatory variables (apart from sex) are at the site
level. This means that a lot of the individuals have exactly the same
combination of all explanatory variables and when there is so many
individuals with 0's it leaves very little power.
When I reduce the model I find that I can remove a number of interactions
terms without really affecting the AIC which lead me to be slightly
concerned.
One option would be to analyses the data at the site level, i.e parasite
prevalence, rather than the probability of being infested.
Any advice as to how to deal with this unbalanced data set would be very
much appreciated.
Anna Renwick
Institute of Biological & Environment Sciences
University of Aberdeen
Zoology Building
Tillydrone Avenue
Aberdeen
AB24 2TZ
The University of Aberdeen is a charity registered in Scotland, No
SC013683.
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