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: [EMAIL PROTECTED] > 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.
