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? -- PGP Public key ID: 1024D/2DE827B3 fingerprint = 8797 A26D 0854 2EAB 0285 A290 8A67 719C 2DE8 27B3 See http://pgp.mit.edu or any PGP keyserver for public key.
signature.asc
Description: Digital signature
_______________________________________________ pspp-dev mailing list [email protected] http://lists.gnu.org/mailman/listinfo/pspp-dev
