When the group means are close together, the labels will overlap.
This overlap is actually informative, indicating that the groups are close.
For this common case, we provide the tiebreaker function

matchMMC

which is also documented and illustrated on the ?MMC page.

I have never tried to put the data on the same scale.  It "should" be easy.
Let me try, and then post an example.

Rich

On Mon, Jan 14, 2013 at 3:53 PM, Karl Ove Hufthammer <karl@huftis.org>wrote:

> må. den 14. 01. 2013 klokka 13.58 (-0500) skreiv Richard M. Heiberger:
> > Please look at the MMC (Mean-mean Multiple Comparisons) plot in the HH
> > package. It displays both the means and the differences.
> >
> > install.packages("HH") ## if you don't already have it.
> > library(HH)
> > ?MMC
>
> Thanks for the suggestion. That’s a very interesting and clever way of
> displaying both means and differences. It’s not what I was looking for,
> though, as it doesn’t display the actual data.
>
> For the record, here’s the syntax for using MMC on the dataset mentioned
> in my original posting:
>
>     l.mmc=mmc(l, linfct = mcp(trt = "Tukey"))
>     plot(l.mmc)
>
> (It looks best on data where the group means aren’t very close;
> otherwise the labels might overlap.)
>
> --
> Karl Ove Hufthammer
>
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