On Aug 3, 2012, at 07:42 , greatest.possible.newbie wrote:
> I am doing multiple comparisons for data that is not normally distributed.
> For this purpose I tried both functions kruskal{agricolae} and
> kruskalmc{pgirmess}. It confuses me that these functions do not yield the
> same results although they are doing the same thing, don't they? Can anyone
> tell my why this happens and which function I can trust?
>
> kruskalmc() tells me that there are no differences between any of the groups
> (i.e. the "difference" column of the results is filled only with FALSE).
> kruskal() tells me that there are indeed differences (between group 4 and
> 11).
Trust nothing if you don't understand the issues involved. There's a reason
that special code is required for multiple comparisons, and a rather
complicated and inexact theory for dealing with it. There are special
complications with rank tests because the standard theory assumes a global null
(no group differences at all).
One of the approaches is to perform the testing pairwise and adjust the
p-values for multiple comparisons. Notice that the kruskal() function has a
p.adj argument which defaults to "none"!
--
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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