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I have performed a repeated measures ANOVA in R, as follows:

aov_velocity = aov(Velocity ~ Material + Error(Subject/(Material)), data=scrd)
summary(aov_velocity)
  • What syntax in R can be used to perform a post hoc test after an ANOVA with repeated measures?
  • Would Tukey's test with Bonferroni correction be appropriate? If so, how could this be done in R?
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see this related question on post hoc tests for repeated measures designs stats.stackexchange.com/questions/575/… – Jeromy Anglim Aug 11 '11 at 10:08
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About your 2nd point: Tukey's HSD already includes a "correction" for multiplicity (at the level of the test statistic, not the alpha level like in Bonferroni's method). So, there's no need to combine both. – chl♦ Aug 11 '11 at 11:35
@chl: so we don't need to correct the alpha level during the multiple pairwise comparisons in the case of Tukey's HSD ? – stan Sep 26 '11 at 3:46
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@stan No. (Note: Unplanned (post-hoc) tests should be performed after the ANOVA showed a significant result, especially if it concerns a confirmatory approach.) – chl♦ Sep 26 '11 at 8:15

1 Answer

up vote 6 down vote accepted

What you could do is specify the model with lme and then use glht from the multcomp package to do what you want. However, lme gives slightly different F-values than a standard ANOVA (see also my recent questions here).

lme_velocity = lme(Velocity ~ Material, data=scrd, random = ~1|Subject)
anova(aov_velocity)

require(multcomp)
summary(glht(lme_velocity, linfct=mcp(Material = "Tukey")), test = adjusted(type = "bonferroni"))

For other contrasts then bonferroni, see e.g., the book on multcomp from the authors of the package.

You may also want to see this post on the R-mailing list, and this blog post for specifying a repeated measures ANOVA in R.

However, as shown in this question from me I am not sure if this approachs is identical to an ANOVA. Furthermore, glht only reports z-values instead of the usual t or F values. This seems to be uncommon, too.

So far, I haven't encountered another way of doing this.

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Thanks a lot! I found your answer very useful! – Luca Sep 3 '11 at 19:42

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