Categorical data analysis is definitely the way you want to go.
Which test you use depends on how you are going to use the results.
For "quick and dirty" I would suggest using Fisher's exact test on all
2x2 submatricies of counts. In this case, with 4 treatments you have
6 possible 2x2 submatricies. See "fishers.test" function.
Another possibility would be a log-linear model, to model Ln(p/q).
Murray M Cooper, Ph.D.
Richland Statistics
9800 N 24th St
Richland, MI, USA 49083
Mail: richs...@earthlink.net
----- Original Message -----
From: "Laura Lucia Prieto Godino" <ll...@cam.ac.uk>
To: <r-help@r-project.org>
Sent: Thursday, February 05, 2009 7:06 AM
Subject: [R] Chi-squared test adjusted for multiple comparisons?
Harbe'stest?
Hi!
I have some data that looks like this
up down percentaje
uew_21 20 14 58.82
uew_20_5 27 40 40.29
uew_20 8 13 38.09
uew_19_5 17 42 28.81
So I have 4 experimental conditions and I am counting number of
animals in the up and down compartment and the calculating the
percentage, I want to know which one of the conditions is different
from each other. If the data wouldn't be percentage I would runt a
kruskal-wallis test to check for general differences and then when
significan a post-hoc test, comparing differents pairs with Man-
Whitney (wilcoxon function in R) with a bonferroni correction for
multiple comparisons. But as the data are in the percentaje form, I
know I need to analize them with either a chi squared or a g-test, but
I have no idea if I can do such a test with many comparissons or how
to do it in R, as well I have seen a paper in which they do something
similar and they are using a Harber's chi squared test. Does anybody
know how to do that in R?
Thank you very much for your help, and thanks to the jim and chuck
for answering my previous statistical question!
Lucia
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