> 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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
