"Sarah Skikne" <[EMAIL PROTECTED]> writes: > Hi, > > I was wondering if it was possible to do the "Scheirer-Ray-Hare" > extension of the Kruskal-Wallis test using R, or if it was possible > to use some other non-parametric test for the following situation: > > I have continuous data that is grouped by 2 factor variables. I > would like a non-parametric test because the group variances are not > equal. I would like to look for the effects of either factor > variable and their interaction.
It is a common misconception that nonparametric tests do not assume equal variances. In fact, they generally assume that entire distributions are the same (under the null hypothesis). Testing for interactions also pretty much assumes effects are on a particular scale, which is not really very different from making parametric assumptions. I'd consider a weighted linear model in such cases, possibly supplemented by simulation or bootstrapping to get an improved estimate of the p-values etc. -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
