Great, thanks a lot, guys!

Only thing is I now have two working versions, that yield *slightly* 
different results.


ACCaov <- aov(Acc ~ Cond + Error(Subj/Cond), WMU3C)
ACClme <- lme(Acc ~ Cond, random = ~1 | Subj/Cond, WMU3C) # what does 
'~1 | Subj/Cond' mean?
summary(glht(ACClme, linfct=mcp(Cond="Tukey")))

yielding

Linear Hypotheses:
            Estimate Std. Error z value p value
2 - 1 == 0 0.392560   0.027210  14.427  <1e-05 ***
3 - 1 == 0 0.400372   0.027210  14.714  <1e-05 ***
3 - 2 == 0 0.007812   0.025442   0.307    0.95


and


ACCaov <- aov(Acc ~ Cond + Error(Subj/Cond), WMU3C)
ACCaov2 <- aov(terms(Acc ~ Subj + Cond, WMU3C))  # gives same result 
as 1st aov, but yields aov not aovlist
ACCtukey <- TukeyHSD(ACCaov2, "Cond"); ACCtukey

yielding

$Cond
          diff         lwr        upr     p adj
2-1 0.3637756  0.29889404 0.42865721 0.0000000
3-1 0.3715881  0.30670654 0.43646971 0.0000000
3-2 0.0078125 -0.05329192 0.06891692 0.9504659


I am trying to work my way through this (so I'm one of the good guys, 
at least I'm trying to understand my stats... ;-)), but any hint to 
what solution may be more appropriate to my problem would be much appreciated.

Cheers,

Ullrich



At 03:16 PM 30/05/2008, you wrote:

>Hi Ullrich,
>
> >> 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.
>
>You want to use lme() in package nlme, then glht() in the multcomp package.
>This will give you multiplicity adjusted p-values and confidence intervals.
>
>## Example
>require(MASS)         ## for oats data set
>require(nlme)         ## for lme()
>require(multcomp)  ## for multiple comparison stuff
>
>Aov.mod <- aov(Y ~ N + V + Error(B/V), data = oats)
>Lme.mod <- lme(Y ~ N + V, random = ~1 | B/V, data = oats)
>
>summary(Aov.mod)
>anova(Lme.mod)
>
>summary(Lme.mod)
>summary(glht(Lme.mod, linfct=mcp(V="Tukey")))
>
>HTH, Mark.
>
>
>Ullrich Ecker wrote:
> >
> > 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: ullrich.ecker@uwa.edu.au
> > Web: www.cogsciwa.com
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
> >
>
>--
>View this message in context: 
>http://www.nabble.com/Tukey-HSD-%28or-other-post-hoc-tests%29-following-repeated-measures-ANOVA-tp17508294p17553029.html
>Sent from the R help mailing list archive at Nabble.com.
>
>______________________________________________
>R-help@r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.

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