would using Kolmogorov-Smirnov test make more sense here? > x=m$Pold > y=m$Pnew > ks.test(x,y)
Two-sample Kolmogorov-Smirnov test data: x and y D = 0.0049066, p-value = 1.221e-15 alternative hypothesis: two-sided Warning message: In ks.test(x, y) : p-value will be approximate in the presence of ties as I understand high p-values here say I cannot claim statistical support for a difference, but low p-values are not evidence of sameness? D should be the maximum difference between the two probability distributions? On Wed, Jun 17, 2020 at 3:06 PM Ana Marija <sokovic.anamar...@gmail.com> wrote: > > Hello, > > I have p values from two distributions, Pold and Pnew > > head(m) > CHR POS MARKER Pnew Pold > 1: 1 785989 rs2980300 0.1419 0.9521 > 2: 1 1130727 rs10907175 0.1022 0.4750 > 3: 1 1156131 rs2887286 0.3698 0.5289 > 4: 1 1158631 rs6603781 0.1929 0.2554 > 5: 1 1211292 rs6685064 0.6054 0.2954 > 6: 1 1478153 rs3766180 0.6511 0.5542 > ... > > In order to compare those two distributions (QQ plots shown in attach) > does it make sense to use: > > var.test(m$Pold, m$Pnew, alternative = "two.sided") > > F test to compare two variances > > data: m$Pold and m$Pnew > F = 0.99937, num df = 1454159, denom df = 1454159, p-value = 0.7057 > alternative hypothesis: true ratio of variances is not equal to 1 > 95 percent confidence interval: > 0.9970808 1.0016750 > sample estimates: > ratio of variances > 0.9993739 > > > Or some other test makes more sense? > > Thanks > Ana ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.