Re: [R] Partek has Dunn-Sidak Multiple Test Correction. Is this the same/similar to any of R's p.adjust.methods?
Earl == Earl F Glynn [EMAIL PROTECTED] on Thu, 14 Jul 2005 12:22:49 -0500 writes: Earl The Partek package (www.partek.com) allows only two selections for Multiple Earl Test Correction: Bonferroni and Dunn-Sidak. Can anyone suggest why Partek Earl implemented Dunn-Sidak and not the other methods that R has? Is there any Earl particular advantage to the Dunn-Sidak method? Earl R knows about these methods (in R 2.1.1): p.adjust.methods Earl [1] holm hochberg hommel bonferroni BH BY fdr Earl [8] none Earl BH is Benjamini Hochberg (1995) and is also called fdr (I wish R's Earl documentation said this clearly). BY is Benjamini Yekutieli (2001). The current R docu has The 'BH' and 'BY' method of Benjamini, Hochberg, and Yekutieli control the false discovery rate, the expected proportion of false discoveries amongst the rejected hypotheses. The false discovery rate is a less stringent condition than the family wise error rate, so these methods are more powerful than the others. so both BH and BY ``are FDR versions''. fdr was used - unfortunately - in some older versions of R, so we kept it working as an *alias* for the time being. You should rather not know about it :-) and use BH or BY (and maybe other methods in the future) instead. Regards, Martin __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
[R] Partek has Dunn-Sidak Multiple Test Correction. Is this the same/similar to any of R's p.adjust.methods?
The Partek package (www.partek.com) allows only two selections for Multiple Test Correction: Bonferroni and Dunn-Sidak. Can anyone suggest why Partek implemented Dunn-Sidak and not the other methods that R has? Is there any particular advantage to the Dunn-Sidak method? R knows about these methods (in R 2.1.1): p.adjust.methods [1] holm hochberg hommel bonferroni BH BY fdr [8] none BH is Benjamini Hochberg (1995) and is also called fdr (I wish R's documentation said this clearly). BY is Benjamini Yekutieli (2001). I found a few hits from Google on Dunn-Sidak, but I'm curious if anyone can tell me on a conservative-liberal scale, where the Dunn-Sidak method falls? My guess is it's less conservative than Bonferroni (but aren't all the other methods?), but how does it compare to the other methods? A limited numerical experiment suggested this order to me: bonferroni (most conservative), hochberg and holm about the same, BY, BH (also called fdr), and then none. Thanks for any of thoughts on this. efg __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
Re: [R] Partek has Dunn-Sidak Multiple Test Correction. Is this the same/similar to any of R's p.adjust.methods?
Earl F. Glynn [EMAIL PROTECTED] writes: The Partek package (www.partek.com) allows only two selections for Multiple Test Correction: Bonferroni and Dunn-Sidak. Can anyone suggest why Partek implemented Dunn-Sidak and not the other methods that R has? Is there any particular advantage to the Dunn-Sidak method? R knows about these methods (in R 2.1.1): p.adjust.methods [1] holm hochberg hommel bonferroni BH BY fdr [8] none BH is Benjamini Hochberg (1995) and is also called fdr (I wish R's documentation said this clearly). BY is Benjamini Yekutieli (2001). I found a few hits from Google on Dunn-Sidak, but I'm curious if anyone can tell me on a conservative-liberal scale, where the Dunn-Sidak method falls? My guess is it's less conservative than Bonferroni (but aren't all the other methods?), but how does it compare to the other methods? As far as I gather, D-S is exact for independent tests, conservative for comparisons of group means, and liberal for mutually exclusive tests (in which case Bonferroni is exact). It is always less conservative than Bonferroni, but the difference is small for typical significance levels: when the Bonferroni level is p, the D-S level is 1 - (1-p/N)^N and if you put p=0.05 and vary N you'll find that it varies from 0.05 at N=1 down to 0.04877 at N=10. (Exercise for the students: what is the limit as N goes to infinity?) The three H-methods play a somewhat different game, basically by only requiring multiple-testing adjustment for non-significant tests. The FDR methods play yet differently by allowing the per test level to increase with the number of significant tests. A limited numerical experiment suggested this order to me: bonferroni (most conservative), hochberg and holm about the same, BY, BH (also called fdr), and then none. Thanks for any of thoughts on this. I'd expect the differences to be fairly small in scenarios where the global null hypothesis is true (excluding none). The main difference comes in when some of the nulls are actually false. Also, it depends on your definitions: With the exception of BY and none the p.adjust methods agree on the smallest adjusted p value, so have the same familywise error rate under the global null. If you count the total number of rejected tests, then you get a difference due to cascading in the non-bonferroni cases. -- O__ Peter Dalgaard Øster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 __ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
