On Apr 4, 2011, at 17:02 , January Weiner wrote: > Dear all, > > I have an n x n matrix of p-values. The matrix is symmetrical, as it > describes the "each against each" p values of correlation > coefficients. > > How can I best correct the p values of the matrix? Notably, the total > number of the tests performed is n(n-1)/2, since I do not test the > correlation of each variable with itself. That means, I only want to > correct one half of the matrix, not including the diagonal. Therefore, > simply writing > > pmat <- p.adjust( pmat, method= "fdr" ) > # where pmat is an n x n matrix > > ...doesn't cut it. > > Of course, I can turn the matrix in to a three column data frame with > n(n-1)/2 rows, but that is slow and not elegant.
I don't think there's a really elegant way (have a look inside pairwise.table if you care). If you start one step further back, you could just use pairwise.table with a suitably defined comparison function. Otherwise, how about ltri <- lower.tri(pmat) utri <- upper.tri(pmat) pmat[ltri] <- p.adjust(pmat[ltri], method = "fdr") pmat[utri] <- t(pmat)[utri] -- Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ 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.
