similar to: manova permutations and pair-wise contrasts

Hi, I've got a dataset with 7 variables for 8 different species. I'd like to test the null hypothesis of no difference among species for these variables. MANOVA seems like the appropriate test, but since I'm unsure of how well the data fit the assumptions of equal variance/covariance and multivariate normality, I want to use a permutation test. I've been through CRAN looking at

Hi R-users I'm trying to do multivariate analysis of variance of a experiment with 3 treatments, 2 variables and 5 replicates. The procedure adopted in SAS is as follow, but I'm having difficulty in to implement the contrasts for comparison of all treatments in R. I have already read manuals and other materials about manova in R, but nothing about specific contrasts were found in them,

Hi.? There appears to be a bug in R function manova.? My friend and I both ran it the same way as shown below (his run) with the shown data set. His results are shown below. we both got the same results.? I was running with R 2.3.1. I'm not sure what version he used. Thanks very much, David Booth Kent State University -----Original Message----- From: dvdbooth at cs.com To: kberk at

Hi all, I am experimenting the function "manova" in R. I tried it on a few data sets, but I did not understand the result: I used "summary(manova_result)" and "summary(manova_result, test='Wilks')" and they gave a bunch of numbers... But I need the Sum-of-Squares of BETWEEN and WITHIN matrices... How do I read off from the R's manova results? Any

Hello, I had a couple questions about manova modeling in R. I have calculated a manova model, and generated a summary.manova output using both the Wilks test and Pillai test. The output is essentially the same, except that the Wilks lambda = 1 - Pillai. Is this normal? (The output from both is appended below.) My other question is about the use of MANOVA. If I have one variable which has a

Hi, sorry to bother you again, but I can't figure it out myself and I also can't find any in-depth documentation about it... Consider the following SAS code (A1II2... contain the measurements for 40 subjects): proc glm; model A1II2 A1IN2 A1NI2 A1NN2 = /nouni; repeated CONTEXT 2, TARGET_SATZ 2; title "A1 500-900 ms"; This produces not only the univariate ANOVAs, but also a

Dear R-users; Previously I posted a question about the problem of rank deficiency in summary.manova. As somebody suggested, I'm attaching a small part of the data set. #*************************************************** "test" <- structure(.Data = list(structure(.Data = c(rep(1,3),rep(2,18),rep(3,10)), levels = c("1", "2", "3"), class =

Version 0.1-0 of a new package `ffmanova' is now available on CRAN. Comments, suggestions, etc. are welcome. Please use the email address ffmanova (at) mevik.net. The package implements 50-50 MANOVA (Langsrud, 2002) with p-value adjustment based on rotation testing (Langsrud, 2005). The 50-50 MANOVA method is a modified variant of classical MANOVA made to handle several highly correlated

Version 0.1-0 of a new package `ffmanova' is now available on CRAN. Comments, suggestions, etc. are welcome. Please use the email address ffmanova (at) mevik.net. The package implements 50-50 MANOVA (Langsrud, 2002) with p-value adjustment based on rotation testing (Langsrud, 2005). The 50-50 MANOVA method is a modified variant of classical MANOVA made to handle several highly correlated

Can R do a repeated measures MANOVA and tell what dimensionality the statistical variance occupies? I have been using MATLAB and SPSS to do my statistics. MATLAB can do ANOVAs and MANOVAs. When it performs a MANOVA, it returns a parameter d that estimates the dimensionality in which the means lie. It also returns a vector of p-values, where each p_n tests the null hypothesis that the mean

Hello everybody After doing a MANOVA on a bunch of data, I want to be able to make some comment on the amount of variation in the data that is explained by the factor of interest. I want to say this in the following way: XX% of the data is explained by A. I can acheive something like what I want by doing the following: X <- structure(c(9, 6, 9, 3, 2, 7), .Dim = as.integer(c(3,

I would like to test the hypothesis that the difference between pairs, for several variables, is zero. This is easily done separately for each variable with: lm(Y ~ rep(0, nrow(Y))) where Y is a matrix whose columns are the differences for each variable between pair members. However, I would like to get an overall probability across all variables from a Wilks or Pillai-Bartlett statistic as in

The test is manova. I tried to use manova() function, I used the code below:fit <- manova(Y ~ X)summary(fit, test="Wilks")but I get p values for intercept and regression coefficient as in anova() function, not for the hull model. Date: Mon, 7 Feb 2011 00:57:43 -0800 Subject: Re: [R] FW: multivariate regression From: djmuser@gmail.com To: denizsigirli@hotmail.com CC:

Dear r-helpers, I have a query regarding use of contrasts in MANOVA. summary(manova(model)) gives me only result of test for overall difference. Would you be so kind and give me a hint how to get the same test statistics (e.g.Pillai's) and P values for the predefined contrasts? Best regards Ondrej Mikula -- Institute of Animal Physiology and Genetics Academy of Sciences of the Czech

Dear all, I am quite new to R and I am having trouble writing the polynomial contrasts for an ordinal factor in MANOVA. # I have a model such as this fit<-manova(cbind(Y1,Y2,Y3)~Groups,data=Events) # where groups is an ordinal factor with 4 levels # how to set polynomial contrasts for the "Groups" factor ? Thank you very much in advance for any help! Best regards, Mauro -- Dr.

Hi, I'm having difficulty specifying contrasts for a within subjects factor with 3 levels. I can do it correctly for my factors with 2- levels, but i'm not getting the correct results for a 3-level factor. My design has 1 between subjects factor (gp) and 3 within subjects factors. Within factor "w" has 2 levels, within factor "x" has two factors, and within

I work with Windows, R 2.4.1. I'm a beginner with R! After doing a Discriminant Function Analysis, I am trying to run manova to get a measure of significance of my lda results. I want to predict groups 1 through 4 using 78 variables (bad group/var ratio, I know, but I'm just exploring the possibilities right now). I've tried with a test matrix and I get my results fine, so I think

Dear friends, Sorry for this somewhat generically titled posting but I had a question with using contrasts in a manova context. So here is my question: Suppose I am interested in doing inference on \beta in the case of the model given by: Y = X %*% \beta + e where Y is a n x p matrix of observations, X is a n x m design matrix, \beta is m x p matrix of parameters, and e is a

Hi I need to compare the performance of two sludge inertization methods. For that i want make a manova Wilks test. Description of the experiment: After the calcination at different temperatures my calcinated sludge are submeted to the lixiviation test. In my tables i show the concentration of the some elements in the extract phase. The results: Method A (calcination at 1100 C) Chromium

Hello all, Is there an r function that exists that will perform repeated measures MANOVAs? For example, let's say I have 3 DVs, one between-subjects IV, and one within-subjects IV. Based on the documentation for the manova command, a function like that below is not appropriate because it cannot take Error arguments. manova(cbind(DV1,DV2,DV3) ~ BetweenSubjectsIV * WithinSubjectsIV +