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RE: st: RE: Post-Hoc test for Kruskal Wallis
From
"Nick Cox" <[email protected]>
To
<[email protected]>
Subject
RE: st: RE: Post-Hoc test for Kruskal Wallis
Date
Mon, 15 Mar 2010 16:51:46 -0000
Thanks, on behalf of those who wanted it.
In terms of your original question I can see two situations here.
1. The data come as ranks. No comment to add.
2. The data do not come as ranks, but working with ranks is a reaction
to some queasiness about the data, e.g. outliers, skewness, some other
kind of messiness. Even in this situation I would tend to play a bit and
consider transformation vs no transformation, or -glm- with different
link functions. If the substantive conclusion is that the scale is
secondary, you can avoid Kruskal-Wallis. If that the scale is crucial,
you (or your client) may need better data.
Nick
[email protected]
Ricardo Ovaldia
Here it is:
Sokal, R. R. and F. J. Rohlf. 1995. Biometry: the principles and
practice of statistics in biological research. 3rd edition. W. H.
Freeman and Co.: New York.
>
> > From: Nick Cox <[email protected]>
> > Date: Monday, March 15, 2010, 11:22 AM
> > . findit Kruskal
> >
> > turns up what there is. -findit- is a variant on
> -search-,
> > recommended
> > to you in the last thread you started.
> >
> > Minimal name (year) references are deprecated on this
> list.
> > But the
> > procedure recommended in that book is almost
> certainly
> > highly
> > programmable.
>
> Ricardo Ovaldia
>
> > Is there a Post-Hoc test for Kruskal Wallis in Stata?
> > Something like the one proposed by Sokal and Rohlf
> (1995).
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