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How can I run a Holm-Sidak test on a repeated measures anova in R?

MeanSEP is the voltag potential from the result of a paper I have to recreate the statistical testing for in a class. I am looking for a significant difference between the conditions; Baseline, ABCD, DCBA, and 300.

Here is as far as I've gotten:

control1 = data.frame(
  c("m1","m2","m3","m4"),
  c(129.43,152.48,118.79,156.02),
  c(180.85,228.72,257.09,278.37),
  c(198.58,230.5,235.82,304.96),
  c(134.75,159.57,223.4,255.32))
colnames(control1) = c("subject","Control","ABCD","DCBA","300")
control=stack(control1) 

subject = rep(control1$subject,4)        # create the "subject" variable
control[3] = subject                   # add it to the new data frame
rm(subject)                               # clean up your workspace
colnames(control) = c("MeanSEP", "Condition", "subject") 

testc= aov(MeanSEP ~ Condition + Error(subject/Condition), data=control)
summary(testc)
Angus Campbell
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  • The [p.adjust](https://stat.ethz.ch/R-manual/R-patched/library/stats/html/p.adjust.html) function may helpful for you. – Richard Erickson Apr 14 '15 at 17:57
  • I think you need to do a t-test for each comparison and then compare those test results to an ANOVA. However, you really should be figuring out your own [homework](http://www.catb.org/esr/faqs/smart-questions.html#homework). – Richard Erickson Apr 15 '15 at 15:18
  • I realize this thread is dead but I just want to clarify that my professor wanted us to use stack exchange. The whole class was basically a tutorial on how to use R by teaching yourself using online resources including helpful strangers. My prof was trying to teach us how to learn on our own, not how to pump out good mutliple choice scores. Writing the proper code wasn't enough to pass the assignments. We needed to be able to write a short discussion on the problems we were given. How we acquire that information was up to us. – Angus Campbell Mar 12 '18 at 18:22

0 Answers0