similar to: post hoc tests two way repeated measures anova

Hi, I found a problem dealing with repeated measures anova post hoc. I'm desperate in finding how to use it in R. The problem is that an Error term in aov() creates class of aovlist and that's why I cannot use TukeyHSD() which needs aov class. I really appreciate your help. Migle

Hi everyone, I am fairly new to R, and I am aware that others have had this problem before, but I have failed to solve the problem from previous replies I found in the archives. As this is such a standard procedure in psychological science, there must be an elegant solution to this...I think. I would much appreciate a solution that even I could understand... ;-) Now, I want to calculate a

Hi, I was trying to figure out how to do post-hoc tests for Two Way ANOVAs and found the following 2 approaches: a. Do pairwise t-tests (bonferroni corrected) if one finds significance with the ANOVA. Link- http://rtutorialseries.blogspot.com/2011/01/r-tutorial-series-two-way-anova-with.html b. Do TukeyHSD on an aov model Link-

Hi, I am fairly new to R and still trying to figure out how it all works, and I have run into a few issues. I apologize in advance if my questions are a bit basic, I'm also no statistics wizard, so part of my problem my be a more fundamental lack of knowledge in the field. I have a dataset that looks something like this: Week Subj Group Readout 0 1 A 352.2 1 1 A

Hi, what is the appropriate syntax to get the random error correct when performing repeated measures anova with 'lme'. let's say i have 3 independent variables, with 'aov', i would write something like: aov(dep_var~(indep_var1*indep_var2*indep_var3) + Error(subject/(indep_var1*indep_var2*indep_var3)). With 'lme' however, i can't find the right formula. i tried

Greetings all, I've done some ANOVAs and have found significant effects across my groups, so now I have to do some post-hoc tests to ascertain which of the groups is driving the significant effect. Usually one would do something like a Newman-Keuls or Scheffe test to get at this but based on googling and browsing through the r-help archives R doesn't support these and they seem to be

Hello everyone, Like a lot of people, I have been looking for functions in R doing ANOVA (ok) and performing multicomparisons (like Student-Newman-Keuls, etc.). As I have been a little bit disappointed, I have bee looking through the net for such "open source" softwares. I found one in: http://www.statpages.org/miller/openstat/OS4.html I have begun to use it, and it seems good and

Dear all, I have a serious problem in applying Tukey post hoc after a repeated measure ANOVA. I followed the suggestions that I found in this help -list especially this one: //[R] Tukey HSD (or other post hoc tests) following repeated measures ANOVA You want to use lme() in package nlme, then glht() in the multcomp package. This will give you multiplicity adjusted p-values and confidence

Hi, I performed an ANOVA repeated measures but I still can't find any good news regarding the possibility to perform multiple comparisons. Can anyone help me? Thanks Diego Bucci Fisiologia Veterinaria Dipartimento di Scienze Mediche Veterinarie Università degli Studi di Bologna Via Tolara di Sopra, 50 40064 Ozzano dell'Emilia, BO Tel. 00390512097904 mail diego.bucci3@unibo.it

A (late) update to this question: On Fri Aug 17 07:33:29, Henrik Singmann wrote: > Hi Diego, > > I am struggeling with this question also for some time and there does > not seem to be an easy and general solution to this problem. At least I > haven't found one. > However, if you have just one repeated-measures factor, use the solution > describe by me here:

Dear all, how can I perform a post hoc analysis for ANOVA with repeated measures (in presence of a balanced design)? I am not able to find a good example over internet in R...is there among you someone so kind to give me an hint with a R example please? For example, the aov result of my analysis says that there is a statistical difference between stimuli (there are 7 different stimuli). ...I

Hi Everyone, I’m trying to figure out how to get R to analyze this experiment properly. I have a series of subjects each with two legs. Within each leg there are two bones that I am interested in. There are also two treatments that I am interested in. That results in four different combinations of treatments. Obviously, since the subjects only have two legs, they can’t receive each

Hi all I am running a 2-way repeated measure anova with 1 between-subjects factor (Group=treatment, control), and 1 within-subject factor (Time of measurement: time1, time2). I extract the results of the anova with: summary(aov(effect ~ Group*Time + Error=Subj/Time, data=mydata)) Now, this must be clearly a dumb question, but how can I quickly extract in R all the post-hoc t-tests for the

Does anyone have any suggestions for how to test for violation of the sphericity assumption and apply the Huynh-Feldt correction to a repeated-measure model? My model follows the format below: Rep.anova=aov(Y~X1*X2+Error(Subject/(X1*X2),data=DataFile)) I've already looked at the explanations aov() and Error() in Baron's “Notes on the use of R for psychology experiments and

Is there code in R to automatically assign letters to different groups that are found to be statistically significant using a post-hoc test following an ANOVA? For example, let's say I found that relative rates of tree growth were statistically significant between tree species using an ANOVA and then I ran a TukeyHSD post-hoc test to determine which species were statistically

dear r community... it loks like i won't be able to reach homogenity of variance for my dataset, so i end up with welch anova instead of regular anova. documentation on this test is rather scarce, so maybe someone here can enlighten me a bit: - do i understand that no two-way implementation of the welch anova has been developed yet? - is there a post-hoc test for welch anovas implemented in

Hi R users, I google the website and I found that there are three ways to perform repeated measure ANOVA: aov, lme and lmer. http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg58502.html But the questions are which one is good to use and how to do post-hoc test? I use the example that is provided in the above link and I try > tt<-aov(p.pa~group*time+Error(subject/time),data=P.PA)

Hi I have data from an experiment that used a repeated-measures factorial 2x2 design (i.e. each participant contributed data to both levels of both factors). I need a non-parametric version of the repeated-measures factorial ANOVA to analyse the data. SPSS only has non-parametric tests for one-way ANOVAs but I have been told that the test I need can be implemented using the R software.

Dear R people, I have a couple of questions about post-doc analyses for 2 by 2 within subjects ANOVA. I conducted a psycholinguistic study that combined a 2 by 2 design and a latin square design. Specifically, I had 32 items each of which generated 4 conditions. Participants saw each of the 32 items only once: 8 in Condition A, 8 in B, 8 in C, and 8 in D. The table below serves as an example.

Hi all, I'm a potential new user of R and have to know this before I start using it: SPSS does not let you do a Post Hoc analysis on repeated measures data. This is a problem for me, since that is what I will have to do. Will R let me do this? /Fredrik -- ----------------------------------------------------------------- Fredrik Karlsson, Research Student Department of Philosophy and