On Sep 20, 2009, at 9:35 PM, David Winsemius wrote:
On Sep 20, 2009, at 9:05 PM, [email protected] wrote:
Hi there all,
This is my first post to the list and I'll first say a few things:
- R is great!
- The archives of this list have helped me solve all of my problems/
questions so far
- I only know enough statistics "to be dangerous"
I'm looking for a way to do post-hoc tests for the Friedman test. I
have a dataset from a within-subjects design with 5 conditions
where some of the dependent variables are ordinal, resulting from
(summed) likert-scaled questionnaire data.
From what I've read, I could use a wilcox.test on pairs of
conditions and adjust the p level, but is there something in R that
does a better job/automates this.
I've seen references to the npmc package but that doesn't seem to
do what I'm looking for, because it only accepts a data frame with
two columns - i.e. there's no way to specify grouping/subject
identifiers.
Thanks,
There is a worked example in the coin package for using a
permutation test to examine differences after a Friedman test. The
authors, Hothorn , Hornik , van de Wiel, and Zeileis, call this
method the Wilcoxon-Nemenyi-McDonald-Thompson test and cite:
Hollander & Wolfe (1999), page 295
http://finzi.psych.upenn.edu/R/library/coin/html/SymmetryTests.html
A further option just presented itself during a search for an
unrelated question:
The MTP function in the multtest package has a robust=TRUE set of
methods with these equivalencies offered:
t.onesamp or t.pair:
Wilcoxon signed rank, wilcox.test with y=NULL or paired=TRUE,
t.twosamp.equalvar:
Wilcoxon rank sum or Mann-Whitney, wilcox.test,
f: Kruskal-Wallis rank sum, kruskal.test,
f.block: Friedman rank sum, friedman.test,
f.twoway: Friedman rank sum, friedman.test,
http://finzi.psych.upenn.edu/R/library/multtest/html/MTP.html
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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