Hi!
Thanks a lot, works as advertised. If i used Tukey, it even gives raw, Bonferroni- and Tukey-corrected p-values!
Thx for the help,
Christoph Strehblow, MD Department of Rheumatology, Diabetes and Endocrinology Wilhelminenspital, Vienna, Austria [EMAIL PROTECTED]
Am 17.05.2005 um 13:23 schrieb Christoph Buser:
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]
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