Dear Mark,
I would include the repeated measure as the smallest stratum in the random
effects specification:
random=~1|sampleunit/year
Setting up user-defined variance structures should be possible using for
example:
weights=varPower(form=~habitat)
or also try out the available corStruct() classes (found in Pinheiro and Bates
2000)
HTH
Christoph
Mark Na schrieb:
Hello,
We are attempting to use nlme to fit a linear mixed model to explain bird
abundance as a function of habitat:
lme(abundance~habitat-1,data=data,method="ML",random=~1|sampleunit)
The data consist of repeated counts of birds in sample units across multiple
years, and we have two questions:
1) Is it necessary (and, if so, how) to specify the repeated measure
(years)? As written, the above code does not.
2) How can we specify a Toeplitz heterogeneous covariance structure for this
model? We have searched the help file for lme, and the R-help archives, but
cannot find any pertinent information. If that's not possible, can we adapt
an existing covariance structure, and if so how?
Thanks, Mark
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--
Dr. rer.nat. Christoph Scherber
University of Goettingen
DNPW, Agroecology
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D-37073 Goettingen
Germany
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Homepage http://www.gwdg.de/~cscherb1
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