R help - Apr 2011 - Adjusting p values of a matrix

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
Charit?platz 1
D-10117 Berlin, Germany
Web?? : www.mpiib-berlin.mpg.de
Tel? ?? : +49-30-28460514

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.weiner at 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
> Charit?platz 1
> D-10117 Berlin, Germany
> Web?? : www.mpiib-berlin.mpg.de
> Tel? ?? : +49-30-28460514
>
> ______________________________________________
> R-help at 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

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.mes at cbs.dk  Priv: PDalgd at gmail.com

How about

	as.matrix(p.adjust(as.dist(pmat)))


Benno

On 4.Apr.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.
> 
> regards,
> j.
> 
> -- 
> -------- Dr. January Weiner 3 --------------------------------------
> Max Planck Institute for Infection Biology
> Charit?platz 1
> D-10117 Berlin, Germany
> Web   : www.mpiib-berlin.mpg.de
> Tel     : +49-30-28460514
> 
> ______________________________________________
> R-help at 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.
>