Dear Ted, dear Fabio, thank you so much for your suggestions. I found that people applied bonferroni corrections in p-values in Pagel’s lambda, as shown in this paper: http://www.pnas.org/content/106/43/18097.abstract

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In my case, I decide to use p.adjust (x,method=“holm”,n=length(x)) to correct the p-values, hope this would be better. I also did some PCA to reduce the trait dimensions and to avoid trait correlation with each other, and then tested phylogenetic signal for the first several PCs. All the best Ting-Wen -- Ting-Wen Chen J.F. Blumenbach Institute of Zoology and Anthropology Georg August University Goettingen Berliner Str. 28 D-37073 Goettingen, Germany Tel: +49-55139-10943 r-sig-phylo-requ...@r-project.org<mailto:r-sig-phylo-requ...@r-project.org> 於 2016年12月13日 19:00 寫道： Send R-sig-phylo mailing list submissions to r-sig-phylo@r-project.org<mailto:r-sig-phylo@r-project.org> To subscribe or unsubscribe via the World Wide Web, visit https://stat.ethz.ch/mailman/listinfo/r-sig-phylo or, via email, send a message with subject or body 'help' to r-sig-phylo-requ...@r-project.org You can reach the person managing the list at r-sig-phylo-ow...@r-project.org When replying, please edit your Subject line so it is more specific than "Re: Contents of R-sig-phylo digest..." Today's Topics: 1. Re: bonferroni corrections in Blomberg's K and Pagel's lambda (F?bio Machado) ---------------------------------------------------------------------- Message: 1 Date: Tue, 13 Dec 2016 08:49:59 -0200 From: F?bio Machado <macfa...@gmail.com> To: "r-sig-phylo@r-project.org" <r-sig-phylo@r-project.org> Subject: Re: [R-sig-phylo] bonferroni corrections in Blomberg's K and Pagel's lambda Message-ID: <bc3b8326-2692-44b9-94ae-56fc2d28b...@gmail.com> Content-Type: text/plain; charset="UTF-8" Recently I came across a similar issue, but I had a far greater number of repeated tests, 595 actually. If i used 10.000 permutations to access significance, I noticed that I could never reject the null hypothesis. That is because for 10.000 permutations, the minimum p value is 1e-04 and the bonferroni adjusted value is 0.0595. So, instead of using any multiple test corrections, I simply rejected the null-hypothesis when the observed statistic fell completely outside the distribution constructed by simulation. This produced nearly identical results to a parametric approach with bonferroni correction (I was analyzing correlations in that case). I don?t know if that adds to the question initially raised, since for 18 tests, the minimum adjusted pvalues are still lower than 0.05, but this experience led me to believe that applying bonferroni correction to non-parametric p-value estimates is not that straightforward. I don?t know if another multiple-test correction method is more adequate for these cases. Any thoughts would be appreciated. best regards, Fabio Andrade Machado Laborat?rio de Evolu??o de Mam?feros Departamento de Gen?tica e Biologia Evolutiva- USP f.mach...@usp.br <mailto:f.mach...@usp.br> ; macfa...@gmail.com <mailto:macfa...@gmail.com> +55 11 982631029 skype: fabio_a_machado Lattes: http://lattes.cnpq.br/3673327633303737 <http://lattes.cnpq.br/3673327633303737> Google Scholar: http://scholar.google.com/citations?hl=en&user=2l6-VrQAAAAJ <http://scholar.google.com/citations?hl=en&user=2l6-VrQAAAAJ> ResearchGate: https://www.researchgate.net/profile/Fabio_Machado2 <https://www.researchgate.net/profile/Fabio_Machado2> On Dec 11, 2016, at 21:55, Theodore Garland <theodore.garl...@ucr.edu> wrote: Dear Ting-Wen, This is a question about statistical philosophy in general, not specific to tests for phylogenetic signal. How best to correct for making multiple tests with related data is a huge and complicated topic. Another issue is whether your traits are correlated with each other, which would affect views on what would be best to do. In any case, beware that simple Bonferroni correction is probably overly conservative, so perhaps at least try something like sequential Bonferroni correction, if you do attempt correction. (Aside from the points above, I am assuming that the 18 compounds do not add up to 100% of the sample. If they do, then you would only want to analyze 17 of them.) Sincerely, Ted Garland On Sun, Dec 11, 2016 at 2:06 PM, Chen, Ting-Wen < ting-wen.c...@biologie.uni-goettingen.de> wrote: Dear all, I?m analysing some chemical compositions of species and considering them as ?traits?, let?s say, 18 different compounds concentration in 37 species. I test phylogenetic signals in the percentage concentration of these compounds using Blomberg?s K and Pagel?s lambda using the function ?phylosig". In Blomberg?s K I apply randomisation for the traits values on the tree to have a p-value for the corresponding trait and in Pagel?s lambda using likelihood test to get the p-value, resulting in several traits with phylogenetic signals as indicated by both K and lambda. Because phylogenetic signal is tested one by one, i.e. repeating 18 times for 18 compounds. Would you suggest that I have to adjust the p-values using e.g. bonferroni corrections? I have some compounds with p-values for both K and lambda about 0.02 (e.g. compound ?I", K=0.656, lambda=0.633), while some other about 0.002 (compound ?R", K=0.849, lambda=0.817). Is it safe to conclude that compound ?I? also has a phylogenetic signal? Any idea will be very appreciated. Thank you! All the best Ting-Wen -- Ting-Wen Chen J.F. 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