Hey Peter,
I agree that Hotelling's T test, although technically possible for two groups
but rejecting the Ho in this case is not going to convey any meaning.
But I am sure there is a possibility. My assumption is based on using simulated
reference set for each comparison.
-- Vickie
----------------------------------------
> Subject: Re: [R] Hotelling T2 test extension for multigroup data
> From: pda...@gmail.com
> Date: Thu, 9 Feb 2012 14:08:22 +0100
> CC: r-help@r-project.org
> To: is...@live.com
>
>
> On Feb 9, 2012, at 12:11 , Vickie S wrote:
>
> >
> > Hi all,
> > I've got the following matrix :
> >
> > mat <- matrix(rnorm(700), ncol=5, dimnames=list( paste("f", c(1:140),
> > sep="_"), c("A", "B", "C", "D", "E")))
> >
> > I can see that currently most of the multivariate Hotelling T2 tests are
> > limited for application on two groups/samples.
> >
> > I wud appreciate if someone can provide me a suggestion how to implement
> > the same for multiple groups.
> >
>
> Please don't start up a new thread, cloning the same misconceptions as an
> earlier one! It doesn't help, you will only get people misunderstanding you
> in the same way...
>
> Apparently, you have rows and columns reversed relative to the common layout
> in multivariate analysis. Also, you have only one observation for each of
> your "groups" (species)?
>
> What makes you think that T^2 would work for you if you had only "A" and "B"
> species? I don't think anything will work unless you have either replication
> or some sort of additional assumptions on the covariance structure of your
> 140-dimensional response.
>
> --
> Peter Dalgaard, Professor
> Center for Statistics, Copenhagen Business School
> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
> Phone: (+45)38153501
> Email: pd....@cbs.dk Priv: pda...@gmail.com
>
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