similar to: anova on aov with Error() [long question]

Dear list member, I deperately need an help in performing a MANOVA in R, but I encountered some problems both in the design and in the synthax with R. I conducted a listening experiment in which 16 participants had to rate the audio stimuli along 5 scales representing an emotion (sad, tender, neutral, happy and aggressive). Each audio stimulus was synthesized in order to represent a

Dear all, Type III SS time again. This case trying to reproduce some SPSS (type III) data in R for a repeated measures anova with a betwSS factor included. As I understand this list etc, if I want type III then I can do library(car) Anova(lm.obj, type="III") But for the repeated measures anova, I need to include an Error-term in the aov() call (Psychology-guide from Jonathan Baron)

I have 2 questions on ANOVA with 1 between subjects factor and 2 within factors. 1. I am confused on how to do the analysis with aov because I have seen two examples on the web with different solutions. a) Jon Baron (http://www.psych.upenn.edu/~baron/rpsych/rpsych.html) does 6.8.5 Example 5: Stevens pp. 468 - 474 (one between, two within) between: gp within: drug, dose aov(effect ~ gp * drug *

Dear R-help list, I am trying to do a mixed ANOVA on a 8960 x 5 dataframe. I have 3 factors for which I want to test all main effects and interactions : f1 (40 levels), f2 (7 levels), and f3 (4 levels). I also have a subject factor, subject, and a dependent variable, dv. Some more information about the factors: f2 is a between-subject factor. That is, for each level of f2 there are 8 nested

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

Why would someone use lm and ANOVA (anova(lm(x))) instead of AOV (or the other way around)? The mean squares and sum of squares are the same, but the F values and p-values are slightly different. I am modeling a dependent~independent1*independent2. Thanks, Matt Bridgman [[alternative HTML version deleted]]

I'm a bit confused about the anova/aov functions. Both seem to rely on data models, where the relationship between the dependent variables and the independent variables can be expressed as a formula. In what I am trying to do, all of my independent variables are qualitative, not quantitative. For example, for each of two options, "option A" and "option B" I have

There are anova {stats} and aov in R. It seems that anova takes an object returned by a model fitting function. But I don't see any examples for anova. Can somebody give me a simple example on anova? What is the difference between anova and aov?

Dear useRs, I've just encountered a serious problem involving the F-test being carried out in aov() and anova(). In the provided example, aov() is not making the correct F-test for an hypothesis involving the expected mean square (EMS) of a factor divided by the EMS of another factor (i.e., instead of the error EMS). Here is the example: Expected Mean Square

Dear all, I have a simple (I think) question that is troubling me lately: Is there any main difference between anova() command and aov() command when performing an ANOVA in Experimental design analyses? Thank you for your time, Ismini

Dear list members, I get the following error when using the glht function to perform a post hoc analysis for an ANOVA with repeated measures: require(nlme) lme_H2H_musicians = lme(H2H ~ Emotion*Material, data=musicians, random = ~1|Subject) require(multcomp) summary(glht(lme_H2H_musicians, linfct=mcp(Type = "Tukey")), test = adjusted(type = "bonferroni")) Error in

Hello everybody, problem solved, there was a typo. I wrote Type instead of Material Best ----Messaggio originale---- Da: angelo.arcadi@virgilio.it Data: 22-giu-2012 11.05 A: <r-help@r-project.org> Ogg: Error with glht function: Error in mcp2matrix(model, linfct = linfct) : Variable(s) 'Type' have been specified in 'linfct' but cannot be found in 'model'!

Hi, there I'm trying to get the value of the Mean Square from the ANOVA model summary that comes from specifying the error term, and am wondering if one can actually do this ( I know it's possible when using anova(lm) objects and the like, but I'm having a tough time with it under this framework). There does appear to be some indexing in the output of this type, but perhaps not

I have a data frame something like: name wrist nLevel emot 1 4094 3.34 1 frustrated 2 4094 3.94 1 frustrated 3 4094 NA 1 frustrated 4 4094 3.51

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 noticed something strange when I ran aov and anova. vtot=c(7.29917, 7.29917, 7.29917) #identical values fac=as.factor(c(1,1,2)) #group 1 has first two elements, group 2 has the 3rd element When I run: > anova(lm(vtot~fac)) Analysis of Variance Table Response: vtot Df Sum Sq Mean Sq F value Pr(>F) fac 1 1.6818e-30 1.6818e-30 0.3333 0.6667 Residuals 1

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

Hello, I've got what I'd expect to be a pretty simple issue: I fit an aov object using multiple error strata, and would like some significance tests for the contrasts I specified. In this contrived example, I model some test score as the interaction of a subject's gender and two emotion variables (angry, happy, neutral), measured at entry to the experiment (entry) and later

Dear R users, I have trouble obtaining the same results for nested Anova with two fixed factors when using lm and aov functions. The formulas are: > e1=aov(y~x/z) > e2=lm(y~x/z) summary(e1) Df Sum Sq Mean Sq F value Pr(>F) x 47 260.0 5.5 18.0088 < 2.2e-16 *** x:z 195 169.6 0.9 2.8318 < 2.2e-16 *** Residuals 14425

Dear list members, I am new member and fairly new into R world! I hope what I have is not beyond the purpose of this list. I did first search for similar experimental designs without success. I want to perform an ANOVA analysis using the aov() function. I am not 100% sure that I have it right. If anyone can help me, that will be greatly appreciated. My design is not balanced for any of the