similar to: aov and Error documentation

Hi all, I wonder whether, for an anova with multiple error strata, it is possible to produce the same diagnostoc plots than with a single-stratum anova. I can extract the residuals for each stratum with e.g. > resid(split1.aov[["block:plot"]]) > resid(split1.aov[["Within"]]) and then produce qqnorm plots etc manually, but is it possible to get all the plots

Bert, thanks for the reply but I feel that my question is less about statistics and more about R interface. Specifically, because the output of R seems different than other programs (systat, for example, gives a between and a within table instead of a three level one). I am familiar with the connection between mixed models and repeated measures,and how mixed models are essentially replacing the

At any rate: Error(SUBJECT/IV) specifies two random effects: SUBJECT and SUBJECT:IV. This is most easily understood if you conceptually arrange your data in a SUBJECT x IV table: One effect is a set of random errors added to each row, the other is a set of effects added to each cell. If you have more than one observation within each cell, then you need a third set of errors to account for

It is unclear to me how aov() handles non-categorical variables. I mean it works and produces results that I would expect, but I was under impression that ANOVA is only defined for categorical variables. In addition, help(aov) says that it "call to 'lm' for each stratum", which I presume means that it calls to lm() for every group of the categorical variable, however I

I am learning R, and although I have looked in the documentation, I may be asking something obvious. Sorry, if that is the case. In a split-plot design if there is a missing subunit summary gives me a table with two rows for the same factor, one in the error within section and one in the section using error between units. With no data missing the table is "normal". How does one

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

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"

Dear list users, I am trying to learn Repeated measures ANOVA using the aov() interface, but I'm struggling to understand its output. According to tutorials on the web, formula for a repeated measures design is: aov(Y ~ IV+ Error(SUBJECT/IV) ) This formula does work but it returns three strata (Error:SUBJECT, Error: SUBJECT:IV, Error: Within), when I would expect two strata (Within and

Hello, the title says it all. I have an ANOVA model with "Error" term and the functions TukeyHSD or those from the "multcomp" package seem not to work with such a model. Assuming that the object returned from aov() function with multiple strata is a list of aov objects, I tried something like TukeyHSD(aov.1$Within), but this does not work either. Does somebody have a

Hi R-help members, I have read a lot in the Archive about the "Type I" vs "Type III" sum of square. I think I have read confusing post so I want to have a clear idea of the problem. Here is an example. I have 3 groups of subjects of unequal sample size (G1 (n=7), G2 (n=7), G3 (n=4)). for Each subject I have 4 measures corresponding to the crossing of 2 factor (A & B)

I am trying to perform a model 3 ANOVA for a 2 factor (say factor A and factor B) anova in which factor A is fixed and factor B is random. Therefore, the error term for the test of factor A should be the A:B interaction term and the error terms for B and A:B should be the model residual (within) term. I have tried to work out how to specify such error strata using aov, however, I have had

How do we specify a contrast interaction matrix for an ANOVA model? We have a two-factor, repeated measures design, with Cue Direction (2) x Brain Hemisphere(2) Each of these has 2 levels, 'left' and 'right', so it's a simple 2x2 design matrix. We have 8 subjects in each cell (a balanced design) and we want to specify the interaction contrast so that: CueLeft>CueRght

Jorge: FYI, *generally speaking,* queries that are mostly statistical in nature, such as yours, are off topic here -- this list is about R programming help, not statistical help. Having said that, you still may get a useful response here -- the r-help/statistics intersection *is* nonempty. However, if not, 2.5 suggestions: 1. Try posting to r-sig-mixed-models instead. Repeated measures are a

Greetings, The aov() function may mislabel the random effects as in the example below: Has anybody else noticed this? Cordially, Giles Crane, MPH, ASA, NJPHA gilescrane at verizon.net > m2 Call: aov(formula = y ~ ap + pe + Error(ju), data = d) Grand Mean: 77.50667 Stratum 1: ju Terms: ap Sum of Squares 4322.538 Deg. of Freedom 12 13 out of 25 effects not

Hi, I don't quite understand what are the return values of aov. I know that it has 'coefficients'. But I need to know what all the other return values are. Can somebody let me know how to figure them? Value: An object of class 'c("aov", "lm")' or for multiple responses of class 'c("maov", "aov", "mlm",

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

I've recently run into the problem of using aov with nested factors, and wanting to get the type II and III sums of squares. Normally Anova from the car package would do fine, but it doesn't like having an Error included, so my.aov <-aov(Response ~ Treatment + Error(Treatment:Replicate)) Anova(my.aov, type="II") yields Error in Anova(nested.anova) : no applicable method

G'day, Plot doesn't seem to work when I specify block as an error term, but does if I load block into the model as the first factor (see code below). Is there some way to make plot work with the fancier model specification? Also, if anyone knows how to get SEDs for this model I would really like to know. response<-c(rnorm(5,5,2),rnorm(5,12,2),rnorm(5,18,2),rnorm(5,12,2))

Hi, I have been having some trouble using aov to do an anova, probably because I'm not understanding how to use this function correctly. For some reason it always tells me that "Estimated effects may be unbalanced", though I'm not sure what this means. Is the formula I am using written incorrectly? Below is the code I am using along with the data: > my.data response

In Baron and Li's "Notes on the use of R for psychology experiments and questionnaires" http://cran.r-project.org/doc/contrib/rpsych.htm they describe a balanced data set for a drug experiment: "... a test of drug treatment effect by one between-subject factor: group (two groups of 8 subjects each) and two within-subject factors: drug (2 levels) and dose (3 levels). "