On 4 May 2011 15:32, peter dalgaard <pda...@gmail.com> wrote: > > On May 4, 2011, at 15:11 , JP wrote: > >> Peter thanks for the fantastically simple and understandable explanation... >> >> To sum it up... to find the z values of a number of pairwise wilcox >> tests do the following: >> >> # pairwise tests with bonferroni correction >> x <- pairwise.wilcox.test(a, b, alternative="two.sided", >> p.adj="bonferroni", exact=F, paired=T) > > > You probably don't want the bonferroni correction there. Rather p.adj="none". > You generally correct the p values for multiple testing, not the test > statistics. >
Oh, I see thanks... of course since I have 5 groups (samples) and 10 comparisons I still have to correct when quoting p values... > (My sentiment would be to pick apart the stats:::wilcox.test.default function > and clone the computation of Z from it, but presumably backtracking from the > p value is a useful expedient.) > Should this be so onerous for the user [read non-statistician] ? >> # what is the data structure we got back >> is.matrix(x$p.value) >> # p vals >> x$p.value >> # z.scores for each >> z.score <- qnorm(x$p.value / 2) >> > > Hmm, you're not actually getting a signed z out of this, you might want to > try alternative="greater" and drop the division by 2 inside qnorm(). (If the > signs come out inverted, I meant "less" not "greater"...) > But I need a two sided test (changing the alternative would change the hypothesis!)... do I still do this? All my z values are negative.... Is this correct? ______________________________________________ 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.