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 mehrmals im Untersuchungsplan auftritt" (p.
271). Which I (hope to) translate: The Friedman test requires the N
individuals to be reciprocally independent, which means that one
individual cannot occur twice or more times in the research design.
*S*
On 19.02.12 22:04, peter dalgaard wrote:
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
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--
Sascha Vieweg, saschav...@gmail.com
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