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

From: Christoph Buser <buser_at_stat.math.ethz.ch>
Date: Tue 17 May 2005 - 21:23:41 EST

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:

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"))

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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