Hi,=20
=20
it sounds as though you may be able to address this dataset using a general=
ized linear mixed effect model in R - such as glmmPQL -with family =3D pois=
son (count data often follows a poisson distribution). Random effects can =
be listed in order to reflect the nesting in your sampling design. =20
=20
hope this helps
=20
Jonathan> Date: Sat, 12 Jan 2008 15:38:33 -0400> From: [EMAIL PROTECTED]> S=
ubject: [ECOLOG-L] Data set with many many zeros..... Help?> To: [EMAIL
PROTECTED]
ISTSERV.UMD.EDU> > Hello Ecolog - I was wondering if anyone had any advice =
on the following> problem.> > I have a data set that is infested by a plagu=
e of zeros that is causing me> to violate all assumptions of classic parame=
tric testing. These are true> zeros in that the organisms in question did n=
ot occur in my randomly sampled> quadrats. They are not "missing data"> > I=
have a fully nested Hierarchical design> My response variable is density o=
btained from quadrat counts.> my explanatory variables are as follows> > Re=
gion (3 levels-fixed)> Location(Region) (4 levels - random> Site(Location(R=
egion)) (4 levels - random)> > My plan was to analyze the data with a neste=
d anova and then proceed to> calculate variance components to allow me to p=
arse out the variance that> could be attributed to each spatial scale in my=
design. Since it is known> that violations of assumptions severely distort=
variance components in> random factors, i would really like to clean up my=
data set to meet the> assumptions but as of yet i have found no acceptable=
remedial measure.> > Has anyone else run into this problem when analysing =
abundance data. I am> aware of conditional models, but i have no practical =
experience with them> and i am not even sure how to proceed with analysis i=
n that case. I have> been using the R program to tackle this problem and i =
have also found no> advice on the r-help mailing list.> > Thanks for any he=
lp that can be provided> > Stephen Cole> Marine Ecology Lab> Saint Francis =
Xavier University
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