To have A and B crossed within Block you need to have something like
random=list(Block=pdBlocked(list(~1,pdIdent(~A-1),pdIdent(~B-1))))
I believe this will give you a random intercept for each level of block
and then random effects for A nested within Block and B nested within Block.
Not completely sure this is what you want.
Kevin Wright
>
> From: "Prof Brian Ripley" <ripley@stats.ox.ac.uk>
> > You need to specify the nesting, probably by Plant/Wplot/Splot.
>
> Thank you for your answer. However Wplot and Splot are on an equal footing
> and not nested within each other. I think I have a similar design (but
> replicated) as mentioned in "Design and Analysis of Experiments" of Douglas
> C. Montgomery (5th Edition). There on page 583 it is written:
>
> "The strip-split-plot design has had extensive application in the
> agricultural sciences, but if finds occasional use in industrial
> experimentation. In the simplest case we have two factors A and B. Factor A
> is applied to whole plots just as in the standard split-plot design. Then
> factor B is applied to strips (which are really just another set of whole
> plots) that are orthogonal tot the original whole plots used for factor A.
> Figure 13-9 illustrates a situation in which both factors A and B have three
> levels. Note that the levels of factor A are confounded with the whole
> plots, and the levels of factor B are confounded witht the strips (which can
> be thought of as a second set of whole plots).
> B1 B2 B3
> A1
> A2
> A3
>
> Rephrasing my original question in this terminology the model with aov is:
>
> Afit <- aov ( Gas ~ Treatment * FactorA * FactorB
> + Error (Block / (FactorA + FactorB) ), data = Wset)
>
> Block because strip-split design is replicated and Treatment is an
> additional factor assigned randomly to the blocks.
>
> This works fine! Apparently Error() allows to put FactorA and FactorB on an
> equal footing. However this is not possible any more with lme.
>
> Specifically, following statement does not work:
> Afit <- lme ( Gas ~ Treatment * FactorA * FactorB, data = Wset,
> random = ~ 1 | Block / (FactorA + FactorB) )
>
> In vain I tried to find another way, but any attempts results in nesting
> FactorA and FactorB.
>
> Thanks for any help,
>
> Paul Quataert
> Institute for Forestry and Game Management
> Belgium
>
>
> ----- Original Message -----
> From: "Prof Brian Ripley" <ripley@stats.ox.ac.uk>
> To: "quataepa" <paul.quataert@lin.vlaanderen.be>
> Cc: "Snews" <s-news@lists.biostat.wustl.edu>
> Sent: Wednesday, January 19, 2005 2:12 PM
> Subject: Re: [S] Strip-split-plot analysis with lme
>
>
> > On Wed, 19 Jan 2005, quataepa wrote:
> > > Dear S-Plusers,
> > > How to perform a strip-split-plot analysis in S+ (version 6.2) with lme?
> > > Specifically I want to perform following analysis
> > > Afit <- aov ( Gas ~ Treatment * Wplot * Splot +
> > > Error( Plant / (Wplot + Splot) ) , data=Wset)
> > > where Wplot and Splot are the whole plot and strip plot variables.
> > > With aov no problem, however I do no succeed to translate this to lme.
> > > I tried:
> > > Afit <- lme ( Gas ~ Treatment * Wplot * Splot,
> > > random = ~1 | Plant / (Wplot + Splot) , data=Wset)
> > > but this is not allowed by the syntaxis.
>
> > You need to specify the nesting, probably by Plant/Wplot/Splot.
> > Brian D. Ripley, ripley@stats.ox.ac.uk
>
>
>
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