Re: [R] Non-parametric test for repeated measures and post-hoc single comparisons in R?

r-help-bounces@r- > project.org] On Behalf Of saschav...@gmail.com > Sent: Montag, 20. Februar 2012 09:59 > To: peter dalgaard > Cc: r-help@r-project.org > Subject: Re: [R] Non-parametric test for repeated measures and post-hoc > single comparisons in R? > > Thanks, I got

Re: [R] Non-parametric test for repeated measures and post-hoc single comparisons in R?

Thanks, I got it! (And I think I should have googled what "replicated" means!) However, then Bortz, Lienert, Boehnke are imprecise, if not wrong: "Der Friedman-Test setzt voraus, dass die N Individuen wechselseitig unabhängig sind, dass also nicht etwa ein und dasselbe Individuum zweimal oder m

Re: [R] Non-parametric test for repeated measures and post-hoc single comparisons in R?

Repeated measures means that you have multiple measurements on the same individual. Usually, the same person measured at different time points. So if you have N individuals and T times, then you can place your observations in an N*T layout. In this layout, you can have 1 observation per cell o

Re: [R] Non-parametric test for repeated measures and post-hoc single comparisons in R?

The following post would not answer your question at full, but might give some good code/information: http://www.r-statistics.com/2010/02/post-hoc-analysis-for-friedmans-test-r-code/ Contact Details:--- Contact me: tal.gal...@g

Re: [R] Non-parametric test for repeated measures and post-hoc single comparisons in R?

On 19.02.12 19:31, Tal Galili wrote: The following post would not answer your question at full, but might give some good code/information: http://www.r-statistics.com/2010/02/post-hoc-analysis-for-friedmans-test-r-code/ Thank you, Tal! As you already mentioned, your interesting post supports

[R] Non-parametric test for repeated measures and post-hoc single comparisons in R?

Some attribute x from 17 individuals was recorded repeatedly on 6 time points using a Likert scale with 7 distractors. Which statistical test(s) can I apply to check whether the changes along the 6 time points were significant? set.seed( 123 ) x <- matrix( sample( 1:7, 17*6, repl=T ), nrow =