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 or R > 1 observations. In the former case, the design is referred to as unreplicated. Got it? -pd On Feb 19, 2012, at 19:25 , saschav...@gmail.com wrote: > 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 = 17, byrow = TRUE, > dimnames = list(1:17, paste( 'T', 1:6, sep='' )) > ) > > I found the Friedman test and the Quade test for testing the overall > hypothesis. > > friedman.test( x ) > quade.test( x ) > > However, the R help files, my text books (Bortz, Lienert and Boehnke, 2008; > Köhler, Schachtel and Voleske, 2007; both German), and the Wikipedia texts > differ in what they propose as requirements for the tests. R says that data > need to be unreplicated. I read 'unreplicated' as 'not-repeated', but is that > right? If so, the example, in contrast, in friedman.test() appears to use > indeed repeated measures. Yet, Wikipedia says the contrary that is to say the > test is good especially if data represents repeated measures. The text books > say either (in the same paragraph, which is very confusing). What is right? > > In addition, what would be an appropriate test for post-hoc single > comparisons for the indication which column differs from others significantly? > > Bortz, Lienert, Boehnke (2008). Verteilungsfreie Methoden in der > Biostatistik. Berlin: Springer > Köhler, Schachtel, Voleske (2007). Biostatistik: Eine Einführung für Biologen > und Agrarwissenschaftler. Berlin: Springer > > -- > Sascha Vieweg, saschav...@gmail.com > > ______________________________________________ > R-help@r-project.org mailing list > 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. -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list 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.
