?Greetings,
My dataset consist of the following columns:
Specimen C_flex C_rigid tau_flex tau_rigid R_flex
R_rigid1 0.1782 0.2975 0.3290 0.3223 0.4338
0.51002 0.0527 0.1097 0.1780 0.1038 0.2364
0.1086.....
where C, tau and R are statistical metrics that asses the performance of a
method in two modes, "flex" and "rigid. Essentially my data are
paired,
they consist of 18 specimens which were analysed twice by my method, once
in "flex" mode and once in "rigid" mode, and I quantified
the performance
of each specimen in each mode using 3 statistical metrics (C, tau, R). What
I want is to assess weather the overall performance of the method in the
two modes ("flex", "rigid") is significantly different. Or
in other words,
whether the difference (C_flex, tau_flex, R_flex) vs (C_rigid, tau_rigid,
R_rigid) is statistically significant. Could someone give a hint of what
type of ANOVA I must use in R or point me to a relevant post?
PS: the most relevant R tutorial I found was this:
http://rtutorialseries.blogspot.cz/2011/02/r-tutorial-series-two-way-repeated.html
The author's dataset is like this:
subject schoolAge10 schoolAge15 schoolAge20 workAge10 workAge15
workAge201 1 5 5 3 1
3 52 2 5 5 3 1
3 5
But I am not sure whether he assess the significance of the difference
(schoolAge10, schoolAge15, schoolAge20) vs (workAge10 workAge15,
workAge20), or schoolAge10 vs workAge10 && schoolAge15 vs workAge15
&&
schoolAge20 vs workAge20.
?
thanks in advance,
Thomas
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