similar to: model simplification in repeated anova

Hi all, Perhaps this in an inappropriate post, but I've found a bug in proj I'd like to track down a bit further before making a formal bug report. The example below shows the problem, if you change the rownames proj fails. The problem seems to be that there is a mismatch in the rownames in the qr objects constructed by aov and the rownames that proj is expecting them to have.

Hello dear R members. I have been learning the Anova syntax in order to perform an SS type III Anova with repeated measures designs (thank you Prof. John Fox!) And another question came up: where/what are the (between/within) residuals for my model? ############ Play code: phase <- factor(rep(c("pretest", "posttest", "followup"), c(5, 5, 5)),

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

Dear R community, I'm currently using R to analyze functional Magnetic Resonance Imaging data. Each analysis involves running ~120,000 repeated-measures ANOVAs. I would like to know if there is any automatic way to access the F- and P-value data that are associated with each of these 120,000 ANOVAs. For example, if the summary output (for the 1st ANOVA of 120,000) shows the following value

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 all, I'd like to extract a value from an ANOVA table, but experience the following problem: ### This works: > s.pseudo <- summary(aov(m ~ block + mix*graz,data=split1)) > s.pseudo Df Sum Sq Mean Sq F value Pr(>F) block 2 1114.66 557.33 4.4296 0.04192 * mix 1 6.14 6.14 0.0488 0.82956 graz 2 1.45 0.72 0.0057 0.99427 mix:graz

Hello!!! I'm trying to do multiple ANOVA tests with R (testing the affect off different factors on the same response). As a result I get many ANOVA tables, and I want to extract a list of the "Pr(>F)" from all the tables. Maybe someone have an idea how to do this? Thanks Imri -- View this message in context:

Doea anyone know how to compute components of variance analysis? For example, I have the score of pupils on a test. Each pupil belongs to a school and within each school I may have several classes? How can I estimate the variance of the pupils, schools, classes and the errror variance? Any examples? Any help will be appreciated. Jason Dr. Iasonas Lamprianou Department of Education The

I am using R 1.1 with Redhat 6.2 and RW 1.001 with Win98 (the upkey doesn't work on my IBM either as has been previously reported by others). The function aov doesn't return either the residuals or the residual degrees of freedom for split-plot designs. If you use the following code from Baron and Li's "Notes on the use of R for psycology experiments and questionnaires"

Is there an easy way of converting an aov.summary into a matrix in which the rows are the factor names and the columns are Df, Sum Sq, Mean Sq, F value and Pr. For example, convert Df Sum Sq Mean Sq F value Pr(>F) block 5 343.29 68.66 4.4467 0.015939 * N 1 189.28 189.28 12.2587 0.004372 ** P 1 8.40 8.40 0.5441 0.474904 K

Dear Madame, Dear Sir, I am able to obtain the coefficients from a 'summary' of 'lm', but NOT from a 'summary' of 'aov'. The following example shows my steps. ## Initialize rm(list = ls()) # remove (almost) everything in the working environment utils::data(npk, package="MASS") # get data model <- yield ~ block + N*P*K ## Using lm npk.lm <-

Dear listmembers, I would like to define a class with a slot that takes either an object of class aov or NULL. I have been reading "S4 Classes in 15 pages more or less" and "Lecture: S4 classes and methods" #First I tried with list and NULL setClass(listOrNULL") setIs("list", "listOrNULL") setIs("NULL", "listOrNULL") #doesn't

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

Hi, This might be a minor bug, or it could be that I'm just mis-using the tools (again). If you modify the example for model.tables to introduce an NA, N <- c(0,1,0,1,1,1,0,0,0,1,1,0,1,1,0,0,1,0,1,0,1,1,0,0) P <- c(1,1,0,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,0,1,1,0) K <- c(1,0,0,1,0,1,1,0,0,1,0,1,0,1,1,0,0,0,1,1,1,0,1,0) yield <-

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Dear statistitians / R users, I was told to analyse the effects of the four factors using lm or update for aov. The following is the result from lm. As you can see that in the last few lines enclosed coefficients. 1)Does this mean I can write a formula, like yield =0.26 + 0.03*H + 1.48*T + 0.04*L + 0.004*C 2) in the two levels design, is there any difference between I use (-1, 1) to

Hello, I noticed that model.tables fails when applied to an aov() fit if called inside a function. The problem seems to occur when as.formula is used inside a function on a string containing "<formula> + Error( x / y )" The reason I tried to use as.formula is to generate dynamic calls to aov(). Here is a minimal example illustrating the problem: ## Example test <-

Is there a way to prevent the re-ordering of factors by aov? I do have a three-way interaction that I do want to fit before a two-way interaction (different factors, so they are not nested), but R moves the two-way interaction to the front. I know it generally makes sense to fit the two-way interactions first, but in this case I think I know what I'm doing. + hv

I'm baffled. When I run make check after installing from source, I get a Error 2. From my understanding of how these things work, it would appear to be coming from this (as at the end of base-Ex.Rout.fail: > has.VR <- require(MASS, quietly = TRUE) Attaching package 'MASS': The following object(s) are masked from package:base : confint confint.lm nclass.FD nclass.scott

I am analyzing from a very simple experiment. I have measured plants of two different colours (yellow and purple) in 9 different populations. So, I have two different factors : a fixed effect (Colour with two levels) and a random one (Population with 9 levels). I first analyzed the data with the aov function LargS is the variable aov(formula = LargS ~ Col + Error(Col/Pop)) Terms: