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 = cy,
> 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(~y),
pdIdent(observer-1), pdIdent(set-1))), correlation=corARMA(q = 6), data=cy)
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?)
HTH,
Simon.
>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
>grateful.
>
>
>eal
>
>ps I have already read Pinheiro & Bates, the jan 05 newsletter, and
>several postings.
>
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Simon Blomberg, B.Sc.(Hons.), Ph.D, M.App.Stat.
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