Message-ID: <99134e88-1461-4eed-a0ec-28c0154213c1@k41g2000yqh.googlegroups.com>
Date: 2009-04-24T14:35:51Z
From: Doerte
Subject: Interpreting the results of Friedman test
In-Reply-To: <72872f6f-1a85-4fde-a2fe-9632fc9cdf00@x5g2000yqk.googlegroups.com>
> Anyways, Friedman's test is a replacement for a two-way ANOVA and you
> are comparing it to a one-way analysis, and the latter is likely just wrong.
Okay. Thanks for the hint.
> Try
>
> anova(lm(AUC~as.factor(Condition)+as.factor(Observer),data=dataForANOVA))
This results in p-value = 0.37969. This value is still quite different
from p-value = 1.913e-06, which is the result of friedman.test
(as.matrix(dataForFriedman)).
Is the method friedman.test (version R 2.9.0) working correctly for
certain types of data and hypotheses? Which limitations are known?
@ Jim: Thanks for the link.
Unfortunately, I'm a newbie in statistics, and I'm not sure, which
method can be used instead of the Friedman Test. Do you have an eye on
a certain R-program from this given website?
Doerte