Untested, but if anything, your best bet is likely something like
summary(glht(lme_H2H, linfct=mcp(Emotion = "Tukey")),
test=adjusted("bonferroni"))
should work (despite the question why you'd want to use Bonferroni rather than
Tukey
For a reference, see the book on the topic by the package authors. Might be in
the paper, too, which is given by
citation("multcomp")
HTH, Michael
> -----Original Message-----
> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of
> angelo.arc...@virgilio.it
> Sent: Montag, 6. Juli 2015 16:01
> To: r-help@r-project.org
> Subject: [R] Bonferroni post hoc test in R for repeated measure ANOVA with
> mixed within and between subjects design
>
> Dear List Members,
>
>
>
> I need to perform a Bonferroni post hoc test in R on a table with three within
> subjects factors (Emotion, having 5 levels, Material, having 4 levels, Shoes,
> having 2 levels) and one between subject factor (Musician, having 2 levels).
>
>
> I normally use the Tukey method with the following formula
>
> require(nlme)
> lme_H2H = lme(H2H ~ Emotion*Material*Shoes*Musician, data=scrd,
> random = ~1|Subject)
> require(multcomp)
> summary(glht(lme_H2H, linfct=mcp(Emotion = "Tukey")))
>
>
>
> I am not able to find any reference that explains with an example of R code
> how to perform a post hoc test with the Bonferroni procedure.
> Can anyone provide an example to perform the same post hoc test in the
> code above but with Bonferroni instead of Tukey?
>
>
> Thank you in advance
>
>
>
> Angelo
>
>
> [[alternative HTML version deleted]]
>
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