[R] adjusted p-values with TukeyHSD?

[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.

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 at 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 at gmx.at
>  > 
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-- 
--------------------------------------------
Dr Sander P. Oom
Animal, Plant and Environmental Sciences,
University of the Witwatersrand
Private Bag 3, Wits 2050, South Africa
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