similar to: MANOVA with repeated measurements

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 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 +

Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly

Hi everyone, I'm posting again, since I haven't got an answer (yet :( ). According to R help, manova does not support the inclusion of the Error() term in the formula call. I have repeated measures data for two dependent variables, so this means I can't account for subject variance in time?. Any lights? Thanks in advance, Rodrigo Abt, Department of Economic Studies, SII, Chile.

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 R Masters, I'm an anesthesiology resident trying to make his way through basic statistics. Recently I have been confronted with longitudinal data in a treatment vs. control analysis. My dataframe is in the form of: subj | group | baseline | time | outcome (long) or subj | group | baseline | time1 |...| time6 | (wide) The measured variable is a continuous one. The null hypothesis in

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

Hello all, I have a question on manova in R: I'm using the function "manova()" from the stats package. Is there anything like a stepwise (backward or forward) manova in R (like there is for regression and anova). When I enter: step(Model1, data=Mydata) R returns the message: Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, : no 'drop1'

Hi, sorry if this is explained somewhere but I didn't find anything. How can I use "Anova" from the car package to test a modell without between subject's factors? Suppose I have the following data mat.1 mat.2 mat.3 di ex 1 85 85 88 1 1 2 90 92 93 1 1 3 97 97 94 1 1 4 80 82 83 1 1 5 91 92 91 1 1 6 83 83

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

I am trying to apply a permuation-based MANOVA (Anderson 2001) to a set of morphological data from three ecomorphs of fish reared under two different conditions and measured at two points during ontogeny. I will supply a distance matrix based on Procrustes distances calculated outside of vegan. I have not found an example of a design such as this for adonis. However, I have designed my factors

Dear colleagues, I had a question wrt the car package. How do I evaluate whether a simpler multivariate regression model is adequate? For instance, I do the following: ami <- read.table(file = "http://www.public.iastate.edu/~maitra/stat501/datasets/amitriptyline.dat", col.names=c("TCAD", "drug", "gender", "antidepressant","PR",

Dear list member, I deperately need an help in performing a MANOVA in R, but I encountered some problems both in the design and in the synthax with R. I conducted a listening experiment in which 16 participants had to rate the audio stimuli along 5 scales representing an emotion (sad, tender, neutral, happy and aggressive). Each audio stimulus was synthesized in order to represent a

Hi there, Does anyone know how to extract elements from the table returned by Manova()? Using the univariate equivalent, Anova(), it's easy: a.an<-Anova(lm(y~x1*x2)) a.an$F This will return a vector of the F-values in order of the terms of the model. However, a similar application using Manova(): m.an<-Manova(lm(Y~x1~x2)) m.an$F Returns NULL. So does any attempt at calling the

Dear R fans, I have got a difficult sounding problem. For fitting a linear model using continuous response and then for re-fitting the model after excluding every single variable, the following functions can be used. library(MASS) model = lm(perf ~ syct + mmin + mmax + cach + chmin + chmax, data = cpus) dropterm(model, test = "F") But I am not sure whether any similar functions is

Hello, I have a MANOVA model and I want to test the following hypothesis: LBM = 0 where B is the parameter estimates. Is there any function to do this in R? Cheers, Philippe -- Philippe Hup? Institut Curie, CNRS UMR 144, INSERM U900 26 rue d'Ulm 75005 Paris - France Email : Philippe.Hupe at curie.fr T?l : +33 (0)1 56 24 69 91 Fax: +33 (0)1 56 24 69 11 website :

hi, i am not able to extract the p-values from the Manova function in the car library. I need to use this function in a high-throughput setting and somehow need the p-values produced. Any ideas? Best regards Bettina Kulle Andreassen -- Bettina Kulle Andreassen University of Oslo Department of Biostatistics and Institute for Epi-Gen (Faculty Division Ahus) tel: +47 22851193 +47 67963923

I would like to conduct an extra sum-of -squares test that compares a full MANOVA model (with all 1st order interactions) to a reduced model (no interactions) to determine if I can drop all interactions at the same time. This is analagous to an extra sum-of-squares F-test in ANOVA, but instead using MANOVA. Is there a command in R that does this? If not, is there a command that calculates

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 list, I would like to run an ANCOVA using car::Anova with repeated measures factors, but I can't figure out how to do it. My (between-subjects) covariate always interacts with my within-subject factors. As far as I understand ANCOVA, covariates usually do not interact with the effects of interest but are simply additive (or am I wrong here?). More specifically, I can add a covariate as