Next step in covariance matrix

[John Darrington]

The code currently in the covariance branch should now correctly 
produce a covariance matrix with an arbitrary number of categorical
variables subject to the following provisos:

* Missing values aren't properly handled.  
* No interactions are supported.

I don't think that either of these are going to be particularly
hard to add (if I correctly understand the issues). But I'd like
to get the current functionality thoroughly tested first.

I think the next step should be to get some sample procedures working
(ones which don't need interactions) so that we can solidly test what
we have so far.  After that we can fix up missing value handling, and
add support for interactions.

So what procedures would be best ? ANOVA, MANOVA, UNIANOVA or a subset 
of GLM? And are there any good texts on how to perform anova from a covariance
matrix?  Most seem to assume that the sums of squares have been seperately 
calculated.

Comments?

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