[Rd] p.adjust(<NA>s), was "Re: [BioC] limma and p-values"

From: Martin Maechler <maechler_at_stat.math.ethz.ch>
Date: Sun 09 Jan 2005 - 03:19:23 EST

>>>>> "GS" == Gordon K Smyth <smyth@wehi.edu.au>
>>>>> on Sat, 8 Jan 2005 01:11:30 +1100 (EST) writes:     


    GS> p.adjust() unfortunately gives incorrect results when
    GS> 'p' includes NAs.  The results from topTable are
    GS> correct.  topTable() takes care to remove NAs before
    GS> passing the values to p.adjust().

There's at least one bug in p.adjust(): The "hommel" method currently does not work at all with NAs (and I have an uncommitted fix ready for this bug).
OTOH, the current version of p.adjust() ``works'' with NA's, apart from Hommel's method, but by using "n = length(p)" in the correction formulae, i.e. *including* the NAs for determining sample size `n' {my fix to "hommel" would do this as well}.

My question is what p.adjust() should do when there are NA's more generally, or more specifically which `n' to use in the correction formula. Your proposal amounts to   ``drop NA's and forget about them till the very end''   (where they are wanted in the result), i.e., your sample size `n' would be sum(!is.na(p)) instead of length(p).

To me it doesn't seem obvious that this setting "n = #{non-NA observations}" is desirable for all P-value adjustment methods. One argument for keeping ``n = #{all observations}'' at least for some correction methods is the following "continuity" one:

If only a few ``irrelevant'' (let's say > 0.5) P-values are replaced by NA, the adjusted relevant small P-values shouldn't change much, ideally not at all. I'm really no scholar on this topic, but e.g. for "holm" I think I would want to keep ``full n'' because of the above continuity argument. BTW, for "fdr", I don't see a straightforward way to achieve the desired continuity.
Of course, p.adjust() could adopt the possibility of chosing how NA's should be treated e.g. by another argument ``use.na = TRUE/FALSE'' and hence allow both versions.

Feedback very welcome, particularly from ``P-value experts'' ;-)

Martin Maechler, ETH Zurich

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https://stat.ethz.ch/mailman/listinfo/r-devel Received on Sun Jan 09 02:27:56 2005

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