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Hello, I am interested in parametric multi comparison tests such as Dunnett, Duncan, Tukey, Newman-Keuls, Bonferonni, Scheffe, and non-parametric tests such as Kruskal-Wallis, and Mann-Whitney U. Are there packages that include most of these tests in each category? Many packages exist for an individual test but their outputs vary in great detail (test statistics, p-values, etc.)

Dear List, are there post-hoc tests like Scheffe, LSD, etc. available after ANOVA test is performed with significant F-statistic? I have tried help.search("Scheffe"), but "No documentation found" (and I have most of packages installed). Probably there are such tests in R, and I am just searching badly... My second question is: Which test/method I should use for ANOVA-like

Greetings all, I've done some ANOVAs and have found significant effects across my groups, so now I have to do some post-hoc tests to ascertain which of the groups is driving the significant effect. Usually one would do something like a Newman-Keuls or Scheffe test to get at this but based on googling and browsing through the r-help archives R doesn't support these and they seem to be

Hi, we are just about to evaluate R as a standard statistics package for our institute. We looked around the help - manual, the FAQ, etc. and did not find anything for the topics of random factors in ANOVA, repeated measures in ANOVA, or within subjects designs in R. Could anyone point us to any information concerning - univariate approach to repeated measures anova - multivariate

Hello everybody, shame on me if I have overlooked something (CRAN, StatLib), but I think I've searched carefully. Maybe it's just too obvious to see for me (happens frequently). Is a function available that extracts multiple comparison of means from objects produced by "aov()" ? Sorry if the term is not correct, I translated from german word by word ("Multiple

Hi R-people, I am wanting to run Factorial ANOVA followed by Scheffe tests on some spatial subjective data. I'm comparing X-Y independent coordinates against x-y dependent coordinates. There are only four independent spatial coordinates that form a square. I am wondering whether I am doing the right thing, because there doesn't seem to be a simple way of doing this. I have attempted to

Hello, As a new user of R (less than a month) I have got my hands on several books and am pouting through the net looking for help in gaining understanding of this powerful tool. I am becoming more proficient with using basic functions to conduct basic statistics. I am now looking to learn how to write code. After a few small worthless functions I decided to try to create a function that was

Hi! I use simtest fonction of multcomp package to compile a Dunnett's test. I have 10 treatments and one control group, so i create a matrix with: m<-matrix(0,10,11) m[1,1]<--1 m[1,2]<-1 m[2,1]<--1 m[2,3]<-1 m[3,1]<--1 m[3,4]<-1 m[4,1]<--1 m[4,5]<-1 m[5,1]<--1 m[5,6]<-1 m[6,1]<--1 m[6,7]<-1 m[7,1]<--1 m[7,8]<-1 m[8,1]<--1 m[8,9]<-1

Hello everyone, Like a lot of people, I have been looking for functions in R doing ANOVA (ok) and performing multicomparisons (like Student-Newman-Keuls, etc.). As I have been a little bit disappointed, I have bee looking through the net for such "open source" softwares. I found one in: http://www.statpages.org/miller/openstat/OS4.html I have begun to use it, and it seems good and

Hi, I'm trying to make sense of the options for multiple comparisons options in R. I've found the following options: pairwise.t.test, which provides standard t-tests, with options for choosing an appropriate correction for multiple comparisons TukeyHSD, which provides the usual Tukey test glht(package multcomp), which provides a variety of options >From the help list, it appears

Dear all, Please help me with the R code which compute SCHEFFE TEST Thanking you in advance Kind regards Mangalani Peter Makananisa Statistical Analyst South African Revenue Service (SARS) Segmentation and Research : Data Modelling Tel: +2712 422 7357 Cell: +2782 456 4669 Fax:+2712 422 6579 Please Note: This email and its contents are subject to our email legal notice

All, I have been reading Dr. Harrell's excellent "Regression Modeling Strategies" book and trying out the exercises. I understand that contrast( ) is used to obtain contrasts between two variables for given levels of other nuisance variables; is there a way to use contrast( ) to obtain, for example, Scheffe confidence intervals / hypothesis tests for many post hoc contrasts at

This is maybe not directly an R problem but I have used R to try to solve it so I think somebody may be able to help. I have a mixture model with three components and a quadratic Scheffe polynomial p1x1+p2x2+p3x3+p12x1x2+p13x1x3+p23x2x3 fitted to the response. Now I'd like to compute the mixture corresponding the maximum response. Model for Y1 has the parameters p1=124.02 p2=60.973 p3=41.479

To my understanding, a confidence interval typically covers a single valued parameter. In contrast, a confidence band covers an entire line with a band. In regression, it is quite common to construct confidence and prediction bands. I have found that many people are connecting individual confidence/prediction interval values produced with predict(object,sd.fit=T,type="conf/pred") and

Hello, I send the message again with the data file as txt because it seems not to be accepted as csv in the R-help list. Data comes from a multiyear field experiment in which 4 levels of a treatment (2, 3, 4, 6) are compared to see the effect on yield. It is a randomized complete block design. The SAS code follows: options ls=95; data uno; infile 'data.txt'

We had problems with our mail server. I have no idea whether this message has reached the list or whether there were any replies. So I retry ... ------------------------ Date: Wed, 5 May 1999 16:42:55 +0200 (CEST) From: "Uli Flenker; Raum 704" <uli at pcinternet.biochem.dshs-koeln.de> To: R-Mailing-List <r-help at stat.math.ethz.ch> Subject: ANOVA "ex post"

Hi All: Package TSERIES is stated to depend on MVA. However, there is no MVA package to be found under the list of package sources. Best wishes, ANDREW tseries: Package for time series analysis Package for time series analysis with emphasis on non-linear and non-stationary modelling Version: 0.7-6 Depends: ts, mva, quadprog Date: 2001-08-27 Author: Compiled by Adrian

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

In the model: lm.1 <- lm(variable ~ BLOC + TIL * YEAR , data=selvanera) I found TIL*YEAR interaction significant. Then I am trying to compare means of the different levels of TIL inside every YEAR using: mc.2 <- glht(lm.1, linfct = mcp(TIL*YEAR="Tukey")) summary(mc.2, test = univariate()) but it does not work. There is any way of doing this, like the SLICE option in

*Bioinformatics/Statistics **Postdoctoral Researcher **University of Oxford, UK * An exciting opportunity has arisen for a Postdoctoral Researcher -- Bioinformatics/Statistics to work on the data-mining and knowledge discovery components of the FP7 project "Enabling information re-Use by linking clinical REsearch and Care", EURECA (http://eurecaproject.eu/partners). By generating a