similar to: Sphericity test in R for repeated measures ANOVA

I have 3 questions (below). Background: I am teaching an introductory statistics course in which we are covering (among other things) repeated measures anova. This time around teaching it, we are using R for all of our computations. We are starting by covering the univariate approach to repeated measures anova. Doing a basic repeated measures anova (univariate approach) using aov() seems

I'm an experimental psychologist and when I run ANOVA analysis in SPSS, I normally ask for a test of non-sphericity (Box's M-test). I also ask for output of the corrections for non-sphericity, such as Greenhouse-Geisser and Huhn-Feldt. These tests and correction factors are commonly used in the journals for experimental and other psychology reports. I have been switching from SPSS to R

Hallo! I just started working with R to do the statistical analyses for my diploma thesis. I got two sets of data. Both contain repeated measures. One has only one within-subject factor with four levels. The other has one within-subject factor with two levels and one between-factor with two levels. I want to compute a Mauchly test for both sets and a Levene test for the second set. I

Data set up as one observation/subject looks like (with a total of 10 subjects) Two treatments: shoe type with 3 categories and region with 8 categories ==> 24 "treatment" columns Subject PHallux PMidToes PLatToe PMTH1 PMidMTH PLatMTH PMidfoot PRearfoot LHallux LMidToes LLatToe LMTH1 LMidMTH LLatMTH LMidfoot LRearfoot DHallux DMidToes DLatToe DMTH1 DMidMTH DLatMTH

Wherever I look up the following reference the name of the author is spelled Mauchly contrary to the naming of the R function. Mauchly, J.W., Significance test for sphericity of a normal $n$-variate distribution, Annals of mathematical statistics, 11(1940), p. 204-209. Is this a typo on the original article (which R Core has corrected) or is it a typo in the function name ? Best regards, Tobias

Hi R-users Does anybody know if there are functions or packages in R for sphericity tests like Bartlett's or Mauchly's? Thanks! __________________________________________________________ Eng. Agr., M.Sc. Eduardo Dutra de Armas __________________________________________________________ Centro de Energia Nuclear na Agricultura (CENA/USP) Laboratório de Ecotoxicologia Av.Centenário 303,

Hello and thanks in advance I am running a glm in R the code is as follows with residual diagnostic code below model4<-glm(Biomass~(Treatment+Time+Site)^2, data=bobB, family=quasi(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed

I haven't been able to find an answer on this that's direct, only implied. In several places I have read that when people asked for sphericity tests they were guided toward lme or mlm models. But, there is no direct indication that the lme method is not subject to the sphericity assumption. In fact, it seems like it should be. Its just a linear model that handles random and

To whom it may concern I made some analysis with R using the command Anova. However, I found some problmes with the output obtained by selecting type II o type III sum of squares. Briefly, I have to do a 2x3 mixed model anova, wherein the first factor is a between factor and the second factor is a within factor. I use the command Anova in the list below, because I want to obtain also the sum

Hello Dear R user, I want to conduct a Principal components analysis and I need to run two tests to check whether I can do it or not. I found how to run the KMO test, however i cannot find an R fonction for the Bartlett's test of sphericity. Does somebody know if it exists? Thanks for your help! Thibault [[alternative HTML version deleted]]

[corrected dataset below] Hello everyone, I am trying to do within subjects repeated measures anova followed by the test of sphericity (sample dataset below). I am able to get either mixed model or linear model anova and TukeyHSD, but have no luck with Repeated-Measures Assuming Sphericity or Separate Sphericity Tests. I am trying to follow example from "car" package, but it seems

Hello everyone, I am trying to do within subjects repeated measures anova followed by the test of sphericity (sample dataset below). I am able to get either mixed model or linear model anova and TukeyHSD, but have no luck with Repeated-Measures Assuming Sphericity or Separate Sphericity Tests. I am trying to follow example from "car" package, but it seems that I am not getting something

Is there a function that calculates the power of a repeated-measure ANOVA design, e.g., 2 groups, 4 within-subject factors, an average 0.40 correlation between the 4 within factors, etc. I don't think I can use power.anova.test() because it does not consider corr=0.40. I am hoping that someone has already implemented the method by Muller & Barton (1989, JASA 84: 549-555) on how to

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,

Dear Prof. Baron, thankyou for your pdf paper on using R, at http://www.psych.upenn.edu/~baron/rpsych.pdf I am currently interested in the sphericity notes on pp. 45-47. The equation on p. 46 suggests the following R calculation: D <- k^2 * ( mean(diag(S)) - mean(S) )^2 while the notes in the pdf indicate the following: D <- k^2 * ( mean(S) - mean(diag(S)) )^2 Can you please consider

Dear helpers, I have a 2x2 mixed design with two "groups" (between-subjects) and two presentation-types (within-subjects). The difference between groups is in the order of manipulations: group.CD having first a block of present.type.C and then a block of present.type.D, each block containing 31 trials. group.DC having first a block of present.type.D and then a block of present.type.C,

With respect to calculating the epsilon index of sphericity for ANOVA, discussed on pp. 45-47 of: http://www.psych.upenn.edu/~baron/rpsych.pdf It notes that epsilon is not required for a repeated measures design with only k=2 levels, as the minimum value of epsilon (e) is given by: e = 1/(k-1) so for k=2, we have e = 1 (ie, no correction of the F test df; see p. 46). These notes apply to a

I believe that the following function is a good function for eyeballing sphericity. But, I can't find functions for tests anywhere (g-g or h-f). Anyone who wants to can feel free to use it. It is bad that R does not provide any tests for sphericity AND cannot do a MANOVA on repeated measures (although lme is an alternative add on package). One of these solutions must be provided in the

Hey, Is this right for a sphericity test? x <- mymatrix mycov <- cov(x) bartlett.text (array (mycov), myconditions)

Hi, I'm getting to grips with using R to perform repeat measures analysis of variance and was wondering is there a potted method to obtain Huynh and Feldt or other adjustments for sphericity violations? Thanks Dominic Dr Dominic J Barraclough Dept Neurobiology and Anatomy, University of Rochester, 601 Elmwood Av, Box 603, Rochester NY 14642 tel (716) 2753627 dominic_barraclough at