Re: [R] adjusted p-values with TukeyHSD?

From: Sander Oom <slist_at_oomvanlieshout.net>
Date: Tue 17 May 2005 - 22:27:57 EST

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.

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 came across more multiple comparison info here;

http://www.agr.kuleuven.ac.be/vakken/statisticsbyR/ANOVAbyRr/multiplecomp.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 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
> > chrisxe@gmx.at
> >
> > ______________________________________________
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>
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-- 
--------------------------------------------
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

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Received on Tue May 17 22:33:15 2005

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