> From: Sander Oom > > Hi Chris and Chris, > > I was keeping my eye on this thread as I have also been discovering > multiple comparisons recently. Your instructions are very > clear! Thanks.
One thing to note, though: Multcomp does not do Dunnett's or Tukey's multiple comparisons per se. Those names in multcomp refer to the contrasts being used (comparison to a control for Dunnett and all pairwise comparison for Tukey). The actual methods used are as described in the references of the help pages. > Now I would love to see an R boffin write a nifty function to > produce a > graphical representation of the multiple comparison, like this one: > > http://www.theses.ulaval.ca/2003/21026/21026024.jpg > > Should not be too difficult.....[any one up for the challenge?] I beg to differ: That's probably as bad a way as one can use to graphically show multiple comparison. The shaded bars serve no purpose. Two alternatives that I'm aware of are - Multiple comparison circles, due to John Sall, and not surprisingly, implemented in JMP and SAS/Insight. See: http://support.sas.com/documentation/onlinedoc/v7/whatsnew/insight/sect4.htm - The mean-mean display proposed by Hsu and Peruggia: Hsu, J. C. and M. Peruggia (1994). Graphical representations of Tukey's multiple comparison method. Journal of Computational and Graphical Statistics 3, 143{161 Andy > I came across more multiple comparison info here; > > http://www.agr.kuleuven.ac.be/vakken/statisticsbyR/ANOVAbyRr/m > ultiplecomp.htm > > Cheers, > > Sander. > > Christoph Buser wrote: > > Dear Christoph > > > > You can use the multcomp package. Please have a look at the > > following example: > > > > library(multcomp) > > > > The first two lines were already proposed by Erin Hodgess: > > > > summary(fm1 <- aov(breaks ~ wool + tension, data = warpbreaks)) > > TukeyHSD(fm1, "tension", ordered = TRUE) > > > > Tukey multiple comparisons of means > > 95% family-wise confidence level > > factor levels have been ordered > > > > Fit: aov(formula = breaks ~ wool + tension, data = warpbreaks) > > > > $tension > > diff lwr upr > > M-H 4.722222 -4.6311985 14.07564 > > L-H 14.722222 5.3688015 24.07564 > > L-M 10.000000 0.6465793 19.35342 > > > > > > By using the functions simtest or simint you can get the > > p-values, too: > > > > summary(simtest(breaks ~ wool + tension, data = warpbreaks, > whichf="tension", > > type = "Tukey")) > > > > Simultaneous tests: Tukey contrasts > > > > Call: > > simtest.formula(formula = breaks ~ wool + tension, data = > warpbreaks, > > whichf = "tension", type = "Tukey") > > > > Tukey contrasts for factor tension, covariable: wool > > > > Contrast matrix: > > tensionL tensionM tensionH > > tensionM-tensionL 0 0 -1 1 0 > > tensionH-tensionL 0 0 -1 0 1 > > tensionH-tensionM 0 0 0 -1 1 > > > > > > Absolute Error Tolerance: 0.001 > > > > Coefficients: > > Estimate t value Std.Err. p raw p Bonf p adj > > tensionH-tensionL -14.722 -3.802 3.872 0.000 0.001 0.001 > > tensionM-tensionL -10.000 -2.582 3.872 0.013 0.026 0.024 > > tensionH-tensionM -4.722 -1.219 3.872 0.228 0.228 0.228 > > > > > > > > or if you prefer to get the confidence intervals, too, you can > > use: > > > > summary(simint(breaks ~ wool + tension, data = warpbreaks, > whichf="tension", > > type = "Tukey")) > > > > Simultaneous 95% confidence intervals: Tukey contrasts > > > > Call: > > simint.formula(formula = breaks ~ wool + tension, data = > warpbreaks, > > whichf = "tension", type = "Tukey") > > > > Tukey contrasts for factor tension, covariable: wool > > > > Contrast matrix: > > tensionL tensionM tensionH > > tensionM-tensionL 0 0 -1 1 0 > > tensionH-tensionL 0 0 -1 0 1 > > tensionH-tensionM 0 0 0 -1 1 > > > > Absolute Error Tolerance: 0.001 > > > > 95 % quantile: 2.415 > > > > Coefficients: > > Estimate 2.5 % 97.5 % t value Std.Err. > p raw p Bonf p adj > > tensionM-tensionL -10.000 -19.352 -0.648 -2.582 3.872 > 0.013 0.038 0.034 > > tensionH-tensionL -14.722 -24.074 -5.370 -3.802 3.872 > 0.000 0.001 0.001 > > tensionH-tensionM -4.722 -14.074 4.630 -1.219 3.872 > 0.228 0.685 0.447 > > > > ----------------------------------------------------------------- > > Please be careful: The resulting confidence intervals in > > simint are not associated with the p-values from 'simtest' as it > > is described in the help page of the two functions. > > ----------------------------------------------------------------- > > > > I had not the time to check the differences in the function or > > read the references given on the help page. > > If you are interested in the function you can check those to > > find out which one you prefer. > > > > Best regards, > > > > Christoph Buser > > > > -------------------------------------------------------------- > > Christoph Buser <[EMAIL PROTECTED]> > > Seminar fuer Statistik, LEO C13 > > ETH (Federal Inst. Technology) 8092 Zurich SWITZERLAND > > phone: x-41-44-632-4673 fax: 632-1228 > > http://stat.ethz.ch/~buser/ > > -------------------------------------------------------------- > > > > > > Christoph Strehblow writes: > > > hi list, > > > > > > i have to ask you again, having tried and searched for > several days... > > > > > > i want to do a TukeyHSD after an Anova, and want to get > the adjusted > > > p-values after the Tukey Correction. > > > i found the p.adjust function, but it can only correct > for "holm", > > > "hochberg", bonferroni", but not "Tukey". > > > > > > Is it not possbile to get adjusted p-values after > Tukey-correction? > > > > > > sorry, if this is an often-answered-question, but i > didn�t find it on > > > the list archive... > > > > > > thx a lot, list, Chris > > > > > > > > > Christoph Strehblow, MD > > > Department of Rheumatology, Diabetes and Endocrinology > > > Wilhelminenspital, Vienna, Austria > > > [EMAIL PROTECTED] > > > > > > ______________________________________________ > > > [email protected] mailing list > > > https://stat.ethz.ch/mailman/listinfo/r-help > > > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > > > > ______________________________________________ > > [email protected] mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > > > > -- > > -------------------------------------------- > Dr Sander P. Oom > Animal, Plant and Environmental Sciences, > University of the Witwatersrand > Private Bag 3, Wits 2050, South Africa > Tel (work) +27 (0)11 717 64 04 > Tel (home) +27 (0)18 297 44 51 > Fax +27 (0)18 299 24 64 > Email [EMAIL PROTECTED] > Web www.oomvanlieshout.net/sander > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
