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 post-hoc test following up a within-subjects ANOVA.

The dv is reaction time (RT), there is a 3-level Condition factor 
(Cond; within-subjects), a number of subjects (Subj), and the 
dataframe is called WMU3C.

The model is

 > RT.aov <- aov(RT~Cond + Error(Subj/Cond), WMU3C)

I understand that TukeyHSD only works with an aov object, but that 
RT.aov is an aovlist object.

 > class(RT.aov)
[1] "aovlist" "listof"

I've tried to work around it using the "maiz" example in the MMC 
documentation of the HH package (a solution previously recommended), 
but I couldn't get it to work: My best shot was to calculate another 
aov avoiding the error term (I don't see how this could be a feasible 
approach, but that's how I understood the MMC example) and a contrast 
vector (contrasting conditions 2 and 3):

I have to admit that I don't quite understand what I'm doing here 
(not that you couldn't tell)

 > RT2.aov <- aov(terms(RT~Subj*Cond, WMU3C))
 > Cond.lmat <- c(0,1,-1)
 > Tukey <- glht.mmc(RT2.aov, focus = "Cond", focus.lmat = Cond.lmat)

yielding

Error in mvt(lower = carg$lower, upper = carg$upper, df = df, corr = 
carg$corr,  :
   NA/NaN/Inf in foreign function call (arg 6)
In addition: Warning message:
In cov2cor(covm) : diagonal has non-finite entries

 > Tukey
       height



Thank you very much for your help!

Ullrich


Dr Ullrich Ecker
Postdoctoral Research Associate
Cognitive Science Laboratories
School of Psychology (Mailbag M304)
Room 211 Sanders Building
University of Western Australia
35 Stirling Hwy
Crawley WA 6009
Australia
Office: +61 8 6488 3266
Mobile: +61 4 5822 0072
Fax: +61 8 6488 1006
E-mail: [EMAIL PROTECTED]
Web: www.cogsciwa.com  
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