Hmm, I have my elements (as in chemical elements) as columns and my samples
as rows.  This is the normal way round for all my other analyses.  I think I
figured it out...  I have 6 groups, all of about 10-12 samples and each with
31 elements.  So for each group there are many more elements than samples
and it makes the analysis impossible due to the problems of the singular
covariance matrix, if I've got that right.
Is that the problem?

2008/8/12 S Ellison <S.Ellison@lgc.co.uk>

> Rank deficiency is usually an indication of under-determination, if I've
> got it right.
>
> But something is clearly odd, because with 31-column matrix of 86 rows,
> you should have 86 residuals for each of 31 models, not 31 residuals.
> Could your matrix be the wrong way round?
>
>
> >>> "Gareth Campbell" <gcam032@gmail.com> 11/08/2008 23:38 >>>
> Thanks for that, the error I get when I use manova is this:
>
> Error in summary.manova(fit) : residuals have rank 30 < 31
>
> What does this mean??
>
> When I call the formula I get 31 residuals and 31 residual standard
> errors.
> Not sure why I get this error?
>
> Thanks
>
> Gareth
>
>
> 2008/8/11 S Ellison <S.Ellison@lgc.co.uk>
>
> > test="Wilks" is available in summary.manova, but not in summary.aov;
> > could that be the problem? I find in ?summary.manova the example
> makes a
> > clear distinction between these three summaries...
> >
> >     fit <- manova(Y ~ rate * additive)
> >     summary.aov(fit)           # univariate ANOVA tables
> >     summary(fit, test="Wilks") # ANOVA table of Wilks' lambda
> >     summary(fit)               # same F statistics as single-df
> terms
> >
> > Another common variable in anova using R is the way contrasts are
> set;
> > you might check that with your colleague?.
> >
> > Steve E
> >
> > >>> "Gareth Campbell" <gcam032@gmail.com> 08/10/08 11:43 PM >>>
> > Hi,
> >
> > I'm doing anova on a matrix of multivariate data where I want to
> assess
> > the
> > effect of each column (element).
> >
> > My matrix is 86 rows x 31 columns.  I've created a grouping factor
> of
> > length
> > 86 containing group assignments of 6 types.
> >
> > Then I run:
> >
> > x<- aov(matrix~grouping.factor)
> > summary(aov.fit.raw, test="Wilks")
> >
> > This is working fine enough, but I'm getting different results to
> > someone
> > who I'm comparing with - am I doing what I think I am doing here??
> >
> > What I think I'm doing is - take the first column (element) and then
> > look at
> > that element between the 6 groups and report F, Pvalue etc..., then
> move
> > onto the 2nd column and repeat.
> >
> > Thanks
> >
> >
> >
> > --
> > Gareth Campbell
> > PhD Candidate
> > The University of Auckland
> >
> > P +649 815 3670
> > M +6421 256 3511
> > E gareth.campbell@esr.cri.nz
> > gcam032@gmail.com
> >
> >        [[alternative HTML version deleted]]
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>
> --
> Gareth Campbell
> PhD Candidate
> The University of Auckland
>
> P +649 815 3670
> M +6421 256 3511
> E gareth.campbell@esr.cri.nz
> gcam032@gmail.com
>
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