Dear R helpers, I am trying to understand how to use the independence_test function in the coin package. I think I suffer from a misunderstanding about what the package does. Either that or I do not understand how to use it properly. Specifically, I cannot understand if I can test independence of arbitrary statistics.
Take the following example: set.seed(10) d <- data.frame(y = c(rnorm(10, mean=3, sd = 5), rnorm(10, mean = 4, sd = 4)), x = c(rep("condA", 10), rep("condB", 10))) I've figured out how to do (m.perm <- independence_test(y ~ x, data=d, distribution="exact")) which tells me (I think) that the probability of these data assuming no difference between the two groups is .0026. But unfortunately I don't know what that means. My (limited) understanding of permutation tests is that they can be used with arbitrary test statistics. But the coin documentation indicates that only three teststats can be used: "max", "quad" and "scalar". Without understanding what these are, I don't feel that I understand the test. Questions: 1) What are "max", "quad" and "scalar"? (book/article references would be appreciated) 2) Can I use arbitrary test statistics with coin? For example, can I test the independence of the variances using coin? Thanks, Ista -- Ista Zahn Graduate student University of Rochester Department of Clinical and Social Psychology http://yourpsyche.org ______________________________________________ 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.