>>>>> Xiaoqing Claire Rong-Mullins
>>>>> on Mon, 23 Jul 2018 12:03:55 -0400 writes:
> Dear R contributors,
> I suggest adding a new method to `p.adjust` ("Adjust P-values for Multiple
> Comparisons",
> https://stat.ethz.ch/R-manual/R-devel/library/stats/html/p.adjust.html).
> This new method is published in Benjamini, Krieger, Yekutieli 2016
Adaptive
> linear step-up procedures that control the false discovery rate
> (Biometrika). https://doi.org/10.1093/biomet/93.3.491
> This paper described multiple methods for adjusting p-values, where the
"TST"
> method (Definition 6) performed the best when test statistics are
> positively correlated, per my interpretation. This method can be labeled
as
> "BKY", for the three authors Benjamini, Krieger, Yekutieli.
> I apologize if this is a duplication.
Not at all a duplication. AFAICS this is the first time this is
proposed here. As a matter of fact this seems such a good (and well
confined) suggestion, that I've proposed it as semester project
here, and so with high probability we will get a "BKY" method
for p.adjust() within a few months.
Thank you, indeed, for the proposal!
Best,
Martin
--
Martin <maech...@stat.math.ethz.ch> http://stat.ethz.ch/~maechler
Seminar für Statistik, ETH Zürich HG G 16 Rämistrasse 101
CH-8092 Zurich, SWITZERLAND
phone: +41-44-632-3408 fax: ...-1228 <><
> Best,
> Claire
> Xiaoqing Claire Rong-Mullins
> Bioinformatic Specialist
> Division of Biostatistics
> College of Public Health
> The Ohio State University
> [[alternative HTML version deleted]]
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