> I would like to be able to get p-values between the groups and be able to adjust for multiple comparisons and would appreciate if someone can guide me.
> I did convert my df into a svrepdesign object as follows: > > df<-svrepdesign (data=df1, scale=1, repweights = df1[, 496:995], type="BRR", combined.weights=TRUE, weight=~WTS_P, na.rm=TRUE) > therefore, I have called "df" as a svrepdesign however, from the survey package, the svyranktest is shown with svydesign only and not with svrepdesign. I could consider using other tests such as svyglm but am also having issues with it. This is outside my area. However, as no one else as responded, I'll offer some more comments. Firstly, I'm doubtful the Kruskal Wallis test will give you pairwise p-values. There are other tests for this. It's also possible to create a matrix of p-values, using an arbitrary test, and then use a correction method. However, I recommend caution with this. Secondly, I don't know if the svyranktest() function will work with the svrepdesign object or not. However, if not, I would assume that other functions in the package would work. Either way, I'm wondering if you've created the svrepdesign object correctly. In particular, "weight=~WTS_P" would assign a formula to weights, probably, which doesn't sound right. And "repweights = df1[, 496:995]" looks questionable, because one, is has hundreds of columns, and two, you've already given that data in the first argument. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.