On 07/26/2012 10:45 AM, Tscheulin Thomas wrote:
Hi,
I have a question regarding the nesting structure in linear mixed models of
data, which is spatially and at the same time temporally correlated.
So far I have tried to get around the problem by averaging out the temporal
component but I would really like to keep everything in the model.
Here is the experimental set-up:
We have measured insect abundance in two different islands, each having 5
sites, each site having 4 plots, in which each we have 5 collection points
(traps). The sampling was repeated 5 times. Two times in 2011 and 3 times in
2012.
After averaging the temporal correlation out I composed the following model for
the abundance:
model<-lme(abundance~continous_explanatory_variable,random=~1|island/site/plot/trap,method="REML")
This works fine but I have problems making a model that allows the temporal
component to stay in.
How can I do this using the function lme?
I know with lmer I could do this:
model2<-lmer(abundance~continous_variable+(1|island/site/distance/triplet)+(1|year/round))
but I really want to use the function lme. How can I insert multiple levels of
grouping in lme?
Any help is very much appreciated!
Best,
A bit of googling brought up this, from 10 years ago:
<http://tolstoy.newcastle.edu.au/R/help/02b/2068.html>
I don't think lme has changed that much.
Bob
--
Bob O'Hara
Biodiversity and Climate Research Centre
Senckenberganlage 25
D-60325 Frankfurt am Main,
Germany
Tel: +49 69 798 40216
Mobile: +49 1515 888 5440
WWW: http://www.bik-f.de/root/index.php?page_id=219
Blog: http://blogs.nature.com/boboh
Journal of Negative Results - EEB: www.jnr-eeb.org
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