similar to: Are post-hoc tests being developed for R?

Matt, Here's a Bonferroni-corrected multiple one-sample t-test that I wrote some years ago. It took a while to get it into R, as na.omit doesn't seem to handle vectors and I had to write a quick kludge (na.remove). Another more general point was that I discovered that the help page for t.test gives the name "parameters" for the degrees of freedom, as in S. However, the name

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"

Hi, I have two questions want to ask. 1. If I have a matrix like this, and I want to figure out the rows whose value in the 3rd column are less than 0.05. How can I do it with R. hsa-let-7a--MBTD1 0.528239197 2.41E-05 hsa-let-7a--APOBEC1 0.507869409 5.51E-05 hsa-let-7a--PAPOLA 0.470451884 0.000221774 hsa-let-7a--NF2 0.469280186 0.000231065 hsa-let-7a--SLC17A5

Full_Name: Ludo Pagie Version: 2.8.1 OS: linux Submission from: (NULL) (194.171.7.39) p.adjust in stats seems to have a bug in handling n>length(p) for (at least) the methods 'holm' and 'hochberg'. For method 'holm' the relevant code: i <- 1:n o <- order(p) ro <- order(o) pmin(1, cummax((n - i + 1) * p[o]))[ro] where p is the

> dim(data.sub) [1] 10000 140 #####extracting all differentially express genes########## library(multtest) two_side<- (1-pt(abs(data.sub),50))*2 diff<- mt.rawp2adjp(two_side) all_differ<-diff[[1]][37211:10000,] all_differ #####list of differentially expressed genes########## > probe.names<- + all_differ[[2]][all_differ[[1]][,"BY"]<=0.01] Error in

Hi- Is anyone working on multiple comparisons of means or post-hoc tests (ie: Tukey, Bonferroni) for R? I saw in the winter 98' archives of this mailing list that these tests had not been implemented yet, I was just wondering if I could look foward to having them. ;-) I also looked through the contributed packages and didn't see anything that offered such tests. I guess I could check for

hi list, i have to ask you again, having tried and searched for several days... i want to do a TukeyHSD after an Anova, and want to get the adjusted p-values after the Tukey Correction. i found the p.adjust function, but it can only correct for "holm", "hochberg", bonferroni", but not "Tukey". Is it not possbile to get adjusted p-values after

Hello, I've fitted a parametric survival model by > survreg(Surv(Week, Cens) ~ C(Treatment, srmod.contr), > data = poll.surv.wo3) where srmod.contr is the following matrix of contrasts: prep auto poll self home [1,] 1 1 1.0000000 0.0 0 [2,] -1 0 0.0000000 0.0 0 [3,] 0 -1 0.0000000 0.0 0 [4,] 0 0 -0.3333333 1.0 0 [5,] 0 0

Dear R community I sent a message out a while ago asking for help with multiple comparison tests for ANOVA's, but haven't had any response yet. I'm sending a final desperate plea. If I can't get this done in R I'm going to have to redo a whole lot of stuff in a commercial package, which I'm REALLY not keen to do! My problem is how to implement these tests in R. Below

Estimados herreros, Sabéis si hay algún sitio donde pueda hacer una pregunta sobre estadística, en concreto un diseño experimental. Alguna lista, foros, etc. Ya se que este no es el sitio adecuado para preguntas de estadística, pero por si alguien se pica os la pongo a continuación. Dos tratamientos C y H. Se aplican a una serie de especies (p.e. 10) Se observa la respuesta de las especies a

I append below a suggested update for p.adjust(). 1. A new method "yh" for control of FDR is included which is valid for any dependency structure. Reference is Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165-1188. 2. I've re-named the "fdr" method to "bh" but

Hi, I was trying to figure out how to do post-hoc tests for Two Way ANOVAs and found the following 2 approaches: a. Do pairwise t-tests (bonferroni corrected) if one finds significance with the ANOVA. Link- http://rtutorialseries.blogspot.com/2011/01/r-tutorial-series-two-way-anova-with.html b. Do TukeyHSD on an aov model Link-

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi. I have been using SAS for some time, and now I have discovered R. I am very happy with it, but I have not found out how to perform some of the multiple comparisons I was used to do in SAS. With the SAS/STAT, I generally used the MEANS (for comparison of arithmetic means) and the LSMEANS (for adjusted means) statements of the GLM procedure (I

Hey Guys, I'm trying to install R on an SGI IRIX 5.3 machine. I'm having trouble getting R to use POSIX regular expressions. Here is the error message I get when I run help: > help() Error in gsub(pattern, replacement, x, ignore.case, extended) : POSIX regular expressions not available I looked through the R-help archives and I found a few tips concerning the problem. I tried them

Dear R people, I have a couple of questions about post-doc analyses for 2 by 2 within subjects ANOVA. I conducted a psycholinguistic study that combined a 2 by 2 design and a latin square design. Specifically, I had 32 items each of which generated 4 conditions. Participants saw each of the 32 items only once: 8 in Condition A, 8 in B, 8 in C, and 8 in D. The table below serves as an example.

Dear all, I run a kruskal wallis test and found significant results. Then, I conducted all pairwise comparisons and found no significant results. Could anyone please give me a hint as to why this happens or redirect me towards a specific web page where I can find more info? (I used alpha=5% and made no bonferroni or other correction for the pairwise comparisons) Thank you   Dr. Iasonas

Hello, I am relatively new to using R. I am using R version 2.8.0. I have a program that downloads stock data from Yahoo! Finance and stores it to a text file on my hard drive. The text file contains the date, opening price, high price, low price, closing price, volume and adjusted price (i.e., adjusted for dividends and splits). I want to read and manipulate the data in R. However, when I

dear r community... it loks like i won't be able to reach homogenity of variance for my dataset, so i end up with welch anova instead of regular anova. documentation on this test is rather scarce, so maybe someone here can enlighten me a bit: - do i understand that no two-way implementation of the welch anova has been developed yet? - is there a post-hoc test for welch anovas implemented in

This is more of a general question without data. After doing 'survdiff', from the 'survival' package, on strata including four groups (so 4 curves on a Kaplan Meier curve) you get a chi squared p-value whether to reject the null hypothesis or not. Is there a method to followup with pairwise testing on the respective groups? I have searched the library but have come up with

Hi R-people, I performed controlled experiments to evaluated the seeds germination of two palms under four levels of water treatments. I conducted a generalized linear model (GLM) with a Poisson distribution to verify whether there were significant differences in the number of seed germination (NS-count variable) between treatments and species (explanatory variables). Thus, my model and output