glht is probably what you should be using.  Both TukeyHSD and glht give
essesntially identical confidence intervals for
the example in ?glht.  What aren't you satisfied with?

amod <- aov(breaks ~ tension, data = warpbreaks)
confint(glht(amod, linfct = mcp(tension = "Tukey")))
TukeyHSD(amod)
On Mon, Jan 2, 2012 at 6:19 PM, Anne Aubut <an438516@dal.ca> wrote:

> Hello,
>
> I am trying to determine the most appropriate way to run post-hoc
> comparisons on my lme model.  I had originally planned to use Tukey HSD
> method as I am interested in all possible comparisons between my treatment
> levels.  TukeyHSD, however, does not work with lme.  The only other code
> that I was able to find, and which also seems to be widely used, is glht
> specified with Tukey:
>
> summary(glht(model, linfct=mcp(Treatment="Tukey"))**)
>
> Out of curiosity, I ran TukeyHSD and the glht code for a simple ANOVA and
> found that they had quite different p-values.  If the glht code is not
> running TukeyHSD, what does the "Tukey" in the code specify?  Is using glht
> code appropriate if I am interested in a substitute for TukeyHSD?  Are
> there any other options for multiple comparisons for lme models?  I am
> really interested in knowing if the Tukey contrasts generated from the glht
> code is providing me with appropriate p-values for my post-hoc comparisons.
>
> I feel like I have reached a dead end and am not sure where else to look
> for information on this issue. I would be grateful for any feedback on this
> matter.
>
>
> Anne Cheverie
> M.Sc. Candidate
> Dalhousie University
>
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