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RE: st: logarithmic scales

From   Roger Newson <>
Subject   RE: st: logarithmic scales
Date   Mon, 01 Dec 2003 20:25:44 +0000

At 11:41 01/12/03 -0800, John Wallace wrote (in reply to Nick Cox and myself):

One place where tiny p-values are important is in multiple-comparison tests,
where you're applying some sort of Bonferroni-like correction or venturing
into False Discovery rates and the like.  If you stack enough tests on top
of one another in a given analysis, its likely you'll meet that p-value
cutoff of significance purely by chance...
This is true if "that p-value cutoff of significance" is from an authority-based prior odds, as used in the Kirkwood-Sterne heuristic that I quoted. It is not true if "that p-value cutoff of significance" is a corrected cutoff, arising either from the Bonferroni correction or from a false discovery rate procedure. However, John is right to point out that arbitrarily tiny p-values can be important in such circumstances. Some documents on multiple-test procedures, false discovery rates and their implementation in Stata can be downloaded either from my website (see my signature), using either a browser or the Stata -net- command.

My personal heuristic is that "" occupies no more bytes than "p<0.0001", and may or may not be more informative, depending on what multiple-test procedure you are using and/or what grade of skeptics you are trying to inform. Therefore, I, for one, tend to give p-values an e-format(eg %8.2e in Stata), or at least a general format (eg %8.2g in Stata), which a lot of non-mathematicians find more friendly, rather than use the official Stata log "default" of %5.3f.


Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
King's College London
5th Floor, Capital House
42 Weston Street
London SE1 3QD
United Kingdom

Tel: 020 7848 6648 International +44 20 7848 6648
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or 020 7848 6605 International +44 20 7848 6605

Opinions expressed are those of the author, not the institution.

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