similar to: type 3 aov for repeated measures

Hi all, I search the archive for finding a simple solution for using TukeyHSD with a multistratum aov result (a repeated emasure anova). The Question have been asked but I've found no clear answer. res<-aov(y~Fa*Fb+Error(Subject/(Fa*Fb)) ) I think that the problem is that res is an aovlist object instead of the "aov" object required by TukeyHSD. Is there an easy solution to

Dear all, I'm not very sure on the use of repeated measures in R, so some advice would be very appreciate. Here is a simple example similar to my real problem (R 2.6.0 for windows): Lets supose I have annual tree production measured in 9 trees during 3 years; the 9 trees are located in 3 different mountains (sites), and each tree receive different annual rainfall (different locations). I would

Dear R-help, I'm facing a problem with defining a repeated measures anova with weighted data. Here's the code to reproduce the problem: # generate some data seed=11 rtrep <- data.frame(rt=rnorm(100),ti=rep(1:5,20),subj=gl (20,5,100),we=runif(100)) # model with within factor for subjects/repeated measurements, no problem aov(rt~ti + Error(subj/ti),data=rtrep) #model with weights

Dear R user, I have a question on using R to analyze data with repeated measurements. I have 2 species with several strains (12) per species, each of which has been measured twice with for a given trait. No particular covariance, just two measures. Now I want to analyze the data with an ANOVA (aov) considering these repeated measures to get the MSq and SSq for the species and strain level. I

dear all, I have a problem with a masked object in a package we created here. we make a package for a workflow of internal analysis of microarray data. to create the package we used: > install.packages(pkgs="affyAnalysis", repos=NULL) > R CMD INSTALL affyAnalysis Erzeuge Verzeichnisse ... Erzeuge DESCRIPTION ... Erzeuge NAMESPACE ... Erzeuge Read-and-delete-me ... Kopiere

Dear all, I need to understand a thing in the beheaviour of the two functions aov and anova in the following case involving an analysis of ANOVA with repeated measures: If I use the folowing command I don´t get any problem: >aov1 = aov(response ~ stimulus*condition + Error(subject/(stimulus*condition)), >data=scrd) > summary(aov1) Instead if I try to fit the same model for the

Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a

Hallo! I have data of the following design: NSubj were measured at Baseline (visit 1) and at 3 following time points (visit 2, visit 3, visit 4). There is or is not a treatment. Most interesting is the question if there is a difference in treatment between the results of visit 4 and baseline. (The other time points are also of interest.) The level of significance is alpha=0.0179 (because of an

Hi all, I have a strange problem and rigth now I can't figure out a solution. Trying to calculate an ANOVA with one between subject factor (group) and one within (hemisphere). My dependent variable is source localization (data). My N = 25. My data.frame looks like this: > ML.dist.stack subj group hemisphere data 1 1 tin left 0.7460840 2 2 tin left

I am analyzing data from an experiment with two factors: Carbon (+/-) and O3 (+/-), with 4 replicates of each treatment, and 4 harvests over a year. The treatments are assigned in a block design to individual Rings. I have approaches this as a repeated measures design. Fixed factors are Carbon, O3 and Harvest, with Ring assigned as a random variable. I have performed repeated measures analysis

I calculate an anova test in the following way: expdata<-read.table("/home/dorien/UA/meta-music/optimuse/optimuse1-build-desktop/results/results_processedCP", header=TRUE)

Hi there, some statistical programs (e.g. SPSS) calculate a correction of the degrees of freedom in a repeated measure analysis of variance (see Greenhouse-Geisser (1958) or Huynh-Feld (1976)) by a factor epsilon. This factor is used to correct the deg. of freedom to get a corrected f-test. Is this also possible with R? Thanks, Sven P.S.: I read in the lm help page: singular.ok logical,

Pursuant to a prior "on topic" thread (http://tolstoy.newcastle.edu.au/R/e4/help/08/07/17192.html ) where I found I could not use AOV to perform an anova on my large data set, I'm now trying to code the analysis "by hand" so to speak. However, as demonstrated below, when comparing my attempt to aov() using a smaller data set, I seem to betray some sort of

  Hi all. I'm having a little trouble with the  function "texteval" (session package). I have used "texteval" in the construction of the function "ExpandData1". "ExpandData1" does not work as expected. However, when I run only the inside code of "ExpandData1" I get the right result. Apparently "texteval" is not working when used

Hi, is there a specific/appropriate function/package to perform post hoc tests when running a two way repeated measures anova? I'm looking for something that will be equivalent to the 'TukeyHSD()' for between subjects anova (with 'aov()'). For one way repeated measures anova, the 'pairwise.t.test()' function seems to work correctly but the results are questionable for

Hello, Are there any access functions to the various residual variables that should result from a repeated measures ANOVA ? MyAOVObject$residuals does not exist, and simply printing MyAOVObject gives a very long print of all fields in the result list, many of which I can't see what they are exactly : $error.qr$qraux, for instance. What I would like basically is to inspect those residuals

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

Hi everyone, I'm trying to do a 2-way repeated measures ANOVA with data that looks like this: subject block rep day light response 1 1 1 one L1 5.5 2 1 2 one L1 4.5 3 1 1 one L2 4 4 1 2 one L2 5.1 5 2 1 one L1 5.3 6 2 2 one L1

Hi, all. I have a simple design I'm comparing to output from SPSS. the design is 1 repeated measure (session) and 1 between measure (cond). my dependent measure is rl. here is the data I'm using (in a data.frame): mig <- data.frame(subj=factor(rep(subj,3)), cond=factor(rep(cond,3)), session=factor(c(rep(1,nsubj),rep(2,nsubj),rep(3,nsubj))),

Hi all, I'm doing a Repeated-Measures ANOVA, but I don't know how to test its contrasts or where to find the p-values of its coefficients. I know how to find the coefficient estimates of a contrast, but not how to test these estimates. First I do something like: y.aov <- aov(y ~ fac1 * fac2 + Error(subj/(fac1 * fac2)), data=data) Then, with coef(y.aov) I get the coefficients