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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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