1. This is not an R question, AFAICS. 2. Sounds like a research topic. I don't think there's a meaningful simple answer. I suspect it strongly depends on the model and context.
-- Bert On Mon, Apr 4, 2011 at 8:02 AM, January Weiner <january.wei...@mpiib-berlin.mpg.de> 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. > > regards, > j. > > -- > -------- Dr. January Weiner 3 -------------------------------------- > Max Planck Institute for Infection Biology > Charitéplatz 1 > D-10117 Berlin, Germany > Web : www.mpiib-berlin.mpg.de > Tel : +49-30-28460514 > > ______________________________________________ > 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. > -- "Men by nature long to get on to the ultimate truths, and will often be impatient with elementary studies or fight shy of them. If it were possible to reach the ultimate truths without the elementary studies usually prefixed to them, these would not be preparatory studies but superfluous diversions." -- Maimonides (1135-1204) Bert Gunter Genentech Nonclinical Biostatistics ______________________________________________ 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.
