[R] crossed random fx nlme lme4
Emilio A. Laca
ealaca at ucdavis.edu
Sun Jul 17 23:32:38 CEST 2005
random = pdBlocked( list( pdIdent( ~ y), pdIdent( ~ observer - 1),
pdIdent( ~ set - 1) )
gave me output only when the data was a groupedData. The results are
different depending on whether I specify observer or set as grouping
I am missing something ...
Simon, Prof Bates, thanks for taking the time to reply.
On Jul 15, 2005, at 6:35 AM, Douglas Bates wrote:
> On 7/13/05, Simon Blomberg <blomsp at ozemail.com.au> wrote:
>> At 09:35 AM 14/07/2005, Emilio A. Laca wrote:
>>> I need to specify a model similar to this
>>> lme.formula(fixed = sqrt(lbPerAc) ~ y + season + y:season, data =
>>> random = ~y | observer/set, correlation = corARMA(q = 6))
>>> except that observer and set are actually crossed instead of nested.
>> Does this work for you? (following P&B pp 162-3 and an R-help archive
>> search on "crossed random effects")...
>> fit <- lme(sqrt(lbPerAc) ~ y * season, random=list(pdBlocked
>> pdIdent(observer-1), pdIdent(set-1))), correlation=corARMA(q = 6),
>> lme isn't very well set up for crossed random effects. It's easier
>> in lmer.
>> I don't think lmer can handle alternative correlation structures yet,
>> though. (Prof. Bates?)
> Exactly. Thanks for the summary.
>>> observer and set are factors
>>> y and lbPerAc are numeric
>>> If you know how to do it or have suggestions for reading I will be
>>> ps I have already read Pinheiro & Bates, the jan 05 newsletter, and
>>> several postings.
>>> R-help at stat.math.ethz.ch mailing list
>>> PLEASE do read the posting guide! http://www.R-project.org/
>> Simon Blomberg, B.Sc.(Hons.), Ph.D, M.App.Stat.
>> Centre for Resource and Environmental Studies
>> The Australian National University
>> Canberra ACT 0200
>> T: +61 2 6125 7800 email: Simon.Blomberg_at_anu.edu.au
>> F: +61 2 6125 0757
>> CRICOS Provider # 00120C
>> R-help at stat.math.ethz.ch mailing list
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