similar to: Bonferroni simultaneous confidence intervals for multiple regression

Hi! I need to run a wilcoxon (Mann-whitly, in fact) test with bonferroni correction, as I am running 10 consecutive wilcoxon test not independent, and I know that bonferroni will partially correct for this problem, but I have no idea how to do it with R, I have been looking in the archive but couldn't understand how to do it. The format I am using at the moment is r4_o <- [1]

Please can someone advise me how I can adjust correlations using bonferroni's correction? I am doing manny correlation tests as part of an investigation of the validity/reliability of a psychometric measure. Help would be so appreciated! Cheers, Louise

Hola a todos/as estoy analizando un diseño factorial con una variable intrasujeto y una inter-sujeto. Ambas resultan significativas en el anova y quiero hacer un análisis por pares, pero aún no sé como puedo hacerlo en R. Me interesan ambos Bonferroni y Tukey. ¿Alguien podría indicarme? Gracias [[alternative HTML version deleted]]

I am performing a sequential bonferroni adjustment on the results of an ANCOVA but the equation I have for calculating p-values from the t-values is not working. I can't seem to find it anywhere else. This is the code I have now: 2*(1-pt(t,df)) where t=t-value and df=degrees of freedom from the ANCOVA. Is there an error in the code? maybe another way to find the p-values? Help! -- View this

Hello- I have run an ANOVA on 4 treatments with unequal sample sizes (n=9,7,10 and 10). I want to determine where my sig. differences are between treatments using a Bonferroni test, and have run the code: pairwise.t.test(Wk16, Treatment, p.adf="bonf") I receive an error message stating that my arguments are of unequal length: Error in tapply(x, g, mean, na.rm = TRUE) :

I am not sure if my message made it through, so here it is again! Hi Rer's, R-1.1.0 I have two questions for you: 1) I am trying to complete a multiple comparison test after completing a one-way ANOVA on some data. I think this is pretty reasonable. aov(MetricSubset ~ GeneNameFactor) works pairwise.t.test(MetricSubset,GeneNameSubset,p.adjuxt.method=bonferroni,p ool.sd=FALSE)

Dear all, I am trying to run Wilcoxon Rank-Sum Test with Bonferroni's correction. I have two lists: l0, l1: mapply(function(x,y)wilcox.test(x,y)$p.value, l0, l1) How do I run Bonferroni's correction on mapply? Any help is much apperciated. Thanks, -Raj

Hello. We have a question concerning the nonparametric analysis of a dataset, which resulted in rejection of the null hypothesis (Kruskal-Wallis-test = H-test). In order to find out which sample means actually are statistically different, we want to do multiple comparisons with the Wilcoxon rank sum test (= U-test); the p-level should be corrected according to Bonferroni-Holm. Thus we decided to

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"

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

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 the R mailing lists 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

Dear r-helpers, I have a question about multiple testing. Here an example that puzzles me: All matrixes and contrast vectors are presented in treatment contrasts. 1. example: library(multcomp) n<-60; sigma<-20 # n = sample size per group # sigma standard deviation of the residuals cov1 <- matrix(c(3/4,-1/2,-1/2,-1/2,1,0,-1/2,0,1), nrow = 3, ncol=3, byrow=TRUE, dimnames =

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-

Hello. I have come across a curious result that I cannot explain. Hopefully, someone can explain this. I am doing a 1-way ANOVA with 6 groups (example: summary(aov(y~A)) with A having 6 levels). I get an F of 0.899 with 5 and 15 df (p=0.51). I then do the same analysis but using data only corresponding to groups 5 and 6. This is, of course, equivalent to a t-test. I now get an F of 142.3

Buenos días a todos: Para empezar, y como este es mi primer mensaje a la lista, me presentaré. Mi nombre es Jorge Tornero y trabajo en el Instituto Español de Oceanografía como Ayudante de Investigación. No soy usuario habitual de R pero estoy tomando contacto con él de cara a un proyecto en el que ando involucrado. Mi consulta es: Me interesaría poder seleccionar columnas de un dataframe,

Anyone I'm wondering how to make confidence intervals (bonferroni or simultaneous) when using Manova and Mancova in Splus. I 'm doing manova with four variables on length and four variables on weight (of salmon). The measuring is done on different time points. I'm working on my master in the field between biostatistics and fishery biology. If anyone knows a good book on mancova

A colleague was asking me if R does multi-level modelling as opposed to multiple regression. Since I have no knowledge of multi-level modelling (except 5 minutes googling ) I thought that I would as here. Does are offer any multi-level modeling packages? It looked like arm might be one but I was not sure. Thanks

Hello, Sometimes the looping (using "for") seems to skip some iterations. An example: arg <- matrix(NA,length(seq(.30,.5,.01)),1) for (i in seq(.30,.5,.01)) { arg[i*100-29] <- i } arg What is the problem with this coding, please? Thank you so much, -- Bruno Cara Giovannetti, PhD Candidate Economics Department Columbia University Personal Webpage: www.columbia.edu/~bcg2108

-----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

Hola a todos Estoy trabajando con el package agricolae para realizar pruebas de medias y obtengo un error que no entiendo al trabajar las interacciones. Os explico: Poseo un Diseño Completamente al Azar para el arreglo de tratamientos factorial de la forma 2*2*4. El modelo consta de 6228 observaciones, el esquema para el anova es: A= 2 niveles={2,5} B= 4 niveles={F1,F2,F3,F4} C= 2