Dear Angelo, The Bonferroni p-value is just the ordinary p-value times the number of tests, so, since R supports multiplication, you can apply the Bonferroni adjustment in R. Because Bonferroni tests for multiple comparisons can be very conservative, asking why you want to use them is a fair question.
Best, John ------------------------------------------------ John Fox, Professor McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/ On Tue, 7 Jul 2015 00:50:49 +0200 (CEST) "angelo.arc...@virgilio.it" <angelo.arc...@virgilio.it> wrote: > Dear Michael, > thank you for your answer, however, I am not asking for the tukey > with the bonferroni adjustment, but doing the post hoc with the bonferroni > method. > Apparently this is done easily in SPSS, I am wondering whether it is possible > with R. > > Can anyone help me? > > Thanks in advance > > > Angelo > > > > ----Messaggio originale---- > Da: meyner...@pg.com > Data: 6-lug-2015 17.52 > A: "angelo.arc...@virgilio.it"<angelo.arc...@virgilio.it>, > "r-help@r-project.org"<r-help@r-project.org> > Ogg: RE: [R] Bonferroni post hoc test in R for repeated measure ANOVA with > mixed within and between subjects design > > 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]] > > > > ______________________________________________ > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posting- > > guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
