"Uli Flenker; Raum 704" <uli at biochem.dshs-koeln.de> writes:
> I have to perform Hotteling's T^2 Test - more generally a MANOVA - on a
> set of data. Is there a (simple?) possibility to do it in R?
>
>
> The somewhat obvious way to do it would be
>
> > summary(aov(Y ~ x1 + x2 ... + xn))
>
> where Y would be a two-column matrix.
>
>
> But this does not work in any possible combination of matrix or factor
> dimensions! Is it principally not possible to perform modelling of
> multivariate data using the "~"-operator?
>
> I'm using R 0.62.2 on Linux 2.0.25.
Let's put it this way: It isn't, but it should be...
0.63 will contain some of the pieces, but not all. There's an extended
aov() and objects of class "maov", and in general you can use
matrix-responses. However, all you get from summary and friends are
lists of univariate results. Splus has manova(), which is essentially
just a wrapper for aov() which attaches class "manova" to the result,
but also summary.manova() computing the relevant test statistics. R
doesn't have this yet.
Probably the most practical way to proceed is to calculate generalised
sums of squares and products with
> r<-resid(lm(y~x))
> t(r)%*%r
and then put TW Anderson's book in your lap and calculate Wilk's
lambda and asymptotic approximations of it's distibution. (Hotelling's
T^2 is some trivial transformation of W's lambda and can be converted
to an exact F distributed variable)
--
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
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