similar to: residuals

Dear R users, I am analyzing several response variables (all scaled to [0;1]) using a multivariate linear model. After fitting the model, I set up a hypothesis matrix to test specific contrasts for these response variables; for example: "a always increases significantly more than b when regressed against x". What I am stuck with now is how to calculate the correct F-values (and

I have design with two repeated-measures factor, and no grouping factor. I can analyze the dataset successfully in other software, including my legacy DOS version BMDP, and R's 'aov' function. I would like to use 'Anova' in 'car' in order to obtain the sphericity tests and the H-F corrected p-values. I do not believe the data are truly deficient in rank. I

Hi, I am doing canonical discriminant analysis using candisc function from the candisc package. My input is a table of species distribution (columns = abundance of each species in each sample) in samples that are split by categories (rows), and I want to know whether each category is associated with a particular set of species and their abundances. I have 20 rows (samples) split into 6

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 all, I am getting the following error: Error in linear.hypothesis.mlm(mod, hyp.matrix.1, SSPE = SSPE, V = V, : The error SSP matrix is apparently of deficient rank = 7 < 11 After running: mod.ok <- lm(as.matrix(dat[,-1]) ~ DC, data=dat) (av.ok <- Anova(mod.ok, idata=idata, idesign=~week)) Although if I jitter the data in "dat", the function seems to work. What

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 all, is there anyone who can help me extracting p-values from an Anova object from the car library? I can't seem to locate the p-values using str(result) or str(summary(result)) in the example below > A <- factor( rep(1:2,each=3) ) > B <- factor( rep(1:3,times=2) ) > idata <- data.frame(A,B) > fit <- lm( cbind(a1_b1,a1_b2,a1_b3,a2_b1,a2_b2,a2_b3) ? sex,

Hi, I have encountered this error when attempting a One-way Repeated-measure ANOVA with my data. I have read the "Anova in car: SSPE apparently deficient rank" thread by I'm not sure the within-subject interaction has more degrees of freedom than subjects in my case. I have prepared the following testing script: rm(list = ls())

Thank you for reading. I am trying to get sphericity values, and I understood I need to use mlm, but how do I implement a nested within subject design in mlm? I already read the R newsletter, fox chapter appendix, EZanova, and whatever I could find online. My original ANOVA anova(aov(resp ~ sucrose*citral, random =~1 | subject, data = p12bl, subset = exps==1)) Or anova(aov(resp ~