The graph I put forward is typically used by ecologists to summarize data. It comes down to a simple means plot with error bars. Significant differences of multiple comparisons are then added using the letters a, b, c etc. If two bars have the same letter, they are not significantly different. It can become quite complicated when mean one is different from mean three but not from mean two and mean two is different from mean three but not mean one. You then get: a, ab, c for mean one, two and three respectively.
Of course what is often used does not constitute the best way of doing it.
Sander.
Liaw, Andy wrote:
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:whichf="tension",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,warpbreaks,type = "Tukey"))
Simultaneous tests: Tukey contrasts
Call: simtest.formula(formula = breaks ~ wool + tension, data =whichf="tension",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,warpbreaks,type = "Tukey"))
Simultaneous 95% confidence intervals: Tukey contrasts
Call: simint.formula(formula = breaks ~ wool + tension, data =p raw p Bonf p adjwhichf = "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.tensionM-tensionL -10.000 -19.352 -0.648 -2.582 3.8720.013 0.038 0.034tensionH-tensionL -14.722 -24.074 -5.370 -3.802 3.8720.000 0.001 0.001tensionH-tensionM -4.722 -14.074 4.630 -1.219 3.8720.228 0.685 0.447several days...----------------------------------------------------------------- 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> > i want to do a TukeyHSD after an Anova, and want to getthe adjusted> p-values after the Tukey Correction.for "holm",
> i found the p.adjust function, but it can only correct> "hochberg", bonferroni", but not "Tukey".Tukey-correction?
> > Is it not possbile to get adjusted p-values after> > sorry, if this is an often-answered-question, but ididnīt find it on> the list archive...http://www.R-project.org/posting-guide.html
> > thx a lot, list, Chris
> > > Christoph Strehblow, MD
> Department of Rheumatology, Diabetes and Endocrinology
> Wilhelminenspital, Vienna, Austria
> [EMAIL PROTECTED]
> > ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!______________________________________________
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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 [EMAIL PROTECTED] Web www.oomvanlieshout.net/sander
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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 [EMAIL PROTECTED] 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
