
Dear colleagues,
I would appreciate very much a few minutes of your attention to this
problem.
This is my lmer model:
lmer(sp1minus0  ~ sp2minus0 + … + sp2minus24 + (1|datetime),
data=data)
where the response variable sp1minus0 is the probability in time=0 of
finding animals of species 1 across each of the 450 pixels (50x50m) of
an experimental plot. 
The explanatory variables are the probability of finding animals of
species 2 across the pixels of the plot in time 0, time minus 1hr, minus
2 hr, … , time minus 24hr. The proximity of the species 2 might have a
positive or negative effect on the movements of species 1. 
The random term is an ID for each hour of the study (2 weeks * 24 hrs
period). 
I want to investigate what explanatory variable or variables have the
strongest effect on the response variable. Obviously, there is time
correlation between the explanatory variables so I guess that my
proposed model is too naive to answer my question.  When running this
model I am getting zero variance for the random effect, so now I doubt
about the meaning of using datetime as a random effect.
Any suggestions to deal with this type of analysis?
Many thanks to all that have read this message.
Have a superb day.
Javier 
 
 
Dr. Javier Perez-Barberia
Population and evolutionary ecologist
The Macaulay Institute
Craigiebuckler
Aberdeen 
AB15 8QH
Scotland, UK

Tel: +44(0)1224 395221
e-mail: j.perez-barberia@macaulay.ac.uk
http://www.macaulay.ac.uk
http://www.macaulay.ac.uk/upland

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