Value. A numeric vector of corrected p-values (of the same length as p, with names copied from p). Details. The adjustment methods include the Bonferroni correction (bonferroni) in which the p-values are multiplied by the number of comparisons.Less conservative corrections are also included by Holm (1979) (holm), Hochberg (1988) (hochberg), Hommel (1988) (hommel), Benjamini & Hochberg …
7/20/2013 · BH correction with p.adjust. Dear List, I have been trying to use p.adjust () to do BH multiple test correction and have gotten some unexpected results. I thought that the equation for this was: pBH = p*n/i. where p is the original p value, n is the number of tests and i is the rank of the p value. However when I try and recreate the corrected …
p: numeric vector of p-values (possibly with NAs).Any other R object is coerced by as.numeric.. method: correction method, a character string. Can be abbreviated. n: number of comparisons, must be at least length(p) only set this (to non-default) when you know what you are doing!, The Multiple Testing Correction method. BH is default. See R p.adjust function for options. estmethod: The default method is ‘pearson’ assuming that the data was normalized (at least with Log-2). If the data is not normalized, its recomended setting is ‘spearman’.
11/15/2014 · Now I use Benjamini-Hochberg procedure to calculate adjusted p-values in R : p.adjust (pvalues, method= BH ) (I can use Benjamini and Yekutieli instead for dependence, but lets skip this for now) As far as I understand, this gives me a set of q-values, that is. the adjusted p-value of an individual hypothesis is the lowest level of FDR for …
Section 6: p-value adjustment for multiple comparisons, p.adjust function | R Documentation, 10/4/2015 · Essentially, with the above you convert your data.frame to a matrix then to a vector then adjust the p-values according to all of the values and then re-construct the matrix. The above could be written in base R as: matrix (p.adjust (as.vector (as.matrix (pval)), method=’fdr’),ncol=2) Share. answered Oct 4 ’15 at 14:45.
4/25/2012 · R : unexpected results from p.adjust (FDR) This issue arose when I was trying to use p.adjust to run FDR adjustment on a vector of p-values. The problem was that many of the resultant p-values were identical. I thought this might be some quirk with my data, but I have reproduced this same problem with arbitrary input vectors.
