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

Some attribute x of 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 )

"Unreplicated" just means that each person is observed exactly once at each time point, but not twice of more often. So "unreplicated" $\neq$ "not repeated". For the post-hoc comparisons, this question or this question provide a start. –  caracal Feb 19 '12 at 9:53