similar to: extracting elements from print object of Manova()

Hi, Suppose I have: > summary(manova(plank.man)) Df Pillai approx F num Df den Df Pr(>F) plankton.new[, 1] 1 0.5267 9.8316 6 53 2.849e-07 *** Residuals 58 --- Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 My understanding is the MANOVA summary returns a list.

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

Dear R users, Can anyone tell me how to get the p value out of the output from summary.manova? I tried all the methods I can think of, but failed. Many thanks Yu-Kang _________________________________________________________________ ¥ß§Y¥Ó½Ð MSN Mobile ªA°È¡G¦b±zªº¤â¾÷¤W¦¬µo MSN Hotmail http://msn.com.tw/msnmobile

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 have received the following error from summary.manova: Error in summary.manova(manova.test, test = "Pillai") : residuals have rank 36 < 64 The data is simulated data for 64 variables. The design is a 2*2 factorial with 10 replicates per treatment. Looking at the code for summary.manova, the error involves a problem with qr(). Does anyone have a suggestion as to how to

Hi, Does anyone know what the error message mean? > Boot2.Pillai <- function(x, ind) { + x <- as.matrix(x[,2:ncol(x)]) + boot.x <- as.factor(x[ind, 1]) + boot.man <- manova(x ~ boot.x) + summary(manova(boot.man))[[4]][[3]] + } > > man.res <- manova(as.matrix(pl.nosite) ~ + as.factor(plankton.new[,1]))$residuals > boot2.plank <-

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,

Hello everybody ! I try to obtain in R eigenvectors and canonical analysis on MANOVA results, but I don't find how to process? In particular, I would be interesting to obtain "standardized canonical coefficients" of the canonical variates. There analysis give some information on the correlation between response variates. My data are organised in 2 terms (one is continu, one is a

Hi there, I've hit a bump in writing postscript files with special characters in the WinAnsi encoding on a windows machine. Here's some sample code: ########################################### postscript(file = "test.eps", encoding="WinAnsi.enc", width = 3, height = 5.5, onefile = TRUE, horizontal=FALSE, family = "sans", title =

Dear All, I would be very appreciative of your help with the following 1). I am running multivariate multiple regression through the manova() function (kindly suggested by Professor Venables) and getting two different answers for test=c("Wilks","Roy","Pillai") and tests=c("Wilks","Roy",'"Pillai") as shown below. In the

Hi there, I'm sure there's an easy answer to this, and I can't wait to see it. The question: is there an easy way to sort a data frame by it's row names? My dilemma: I've had to pull apart a data frame, run it through a loop to do some calculations and generate new variables, and then re-construct the chunks back into a data frame at the end. Doing this preserves the row

Hi, My question is how do I gain control over what values the X and Y axis show. Below is a sample plot I have made and want the X axis to represent a time vector with values taking the form Q1.60, Q2.60, Q3.60...Q1.90..etc...Currently the X axis starts with value 0 and increases by 1 through the end of the sample. win.graph() matplot(v.0,log.diff.v.6,type="l",lty=1, col=2,

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 all, Does anyone have any tips for extracting chunks of data from a distance matrix? For instance, if one was interested in only a subset of distance comparisons (i.e., that of rows 4 thru 6, and no others), is there a simple way to pull that data out? >From some playing around with an example (below), I've been able to figure out that a distance matrix in R is stored as a single

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

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

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

Dear friends, I'm stuck with the following problem: I would like to do a multiple regression with muliple dependent variables, and i don't know how to write my formula in the model. Someone in previous messages offered the cbind method, but the result is just as many regression as the number of dependent variables, it is just a time saving method; i'm looking for a method closer to a

Dear all, I need to do a Manova but I have an unbalanced design. I have morphological measurements similar to the iris dataset, but I don't have the same number of measurements for all species. Does anyone know a procedure to do Manova with this kind of input in R? Thank you very much, Naiara. -------------------------------------------- Naiara S. Pinto Ecology, Evolution and Behavior 1