From: Liaw, Andy <andy_liaw_at_merck.com>

Date: Tue 17 May 2005 - 23:19:48 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue May 17 23:27:57 2005

Date: Tue 17 May 2005 - 23:19:48 EST

*> 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 <buser@stat.math.ethz.ch>
**> > 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
**> didnīt find it on
**> > > the list archive...
**> > >
**> > > thx a lot, list, Chris
**> > >
**> > >
**> > > Christoph Strehblow, MD
**> > > Department of Rheumatology, Diabetes and Endocrinology
**> > > Wilhelminenspital, Vienna, Austria
**> > > chrisxe@gmx.at
**> > >
**> > > ______________________________________________
**> > > R-help@stat.math.ethz.ch mailing list
**> > > https://stat.ethz.ch/mailman/listinfo/r-help
**> > > PLEASE do read the posting guide!
**> http://www.R-project.org/posting-guide.html
**> >
**> >
**> ______________________________________________
**> > R-help@stat.math.ethz.ch 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 sander@oomvanlieshout.net
**> Web www.oomvanlieshout.net/sander
**>
**> ______________________________________________
**> R-help@stat.math.ethz.ch mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide!
**> http://www.R-project.org/posting-guide.html
**>
**>
*

>

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Tue May 17 23:27:57 2005

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