Dear S-News Members!
I´ve got a particular problem and I´m not sure if a permutationtest is the
solution to solve it, though I´d intuitively use it.
(1) If I´ve got two samples x= (x1, x2,..., xn) and y= (y1, y2,..., yn) (both
have got the same sample-size n) which I´d like to put together to actually one
big sample.
(2) Then I´d like to draw "without replacement" n elements by chance from the
created whole sample, building the first NEW sample.
(3) All the elements left in the big sample, created before, which weren´t
drawn, build automatically the second NEW sample.
(4) Then I´d like to evuluate to statistic of interest - a
correlation-coefficient.
(5) If I repeat this procedure B=1000 times, then I should get an empirical
estimate of the variability of the correlationcoefficient, which I´m interested
in.
To do the Steps (1) to (5) I´ve used the Permutationtest from the resample -
Library. Here´s the syntax:
> permutationTest(data = XY [c("x", "y")], statistic =
> resampCor(data, resampleColumns = "x"), alternative =
> "two.sided", resampleColumns = "x")
My questions are:
i) Is this the right syntax to do the steps (1) to (5)?
ii) Furhtermore, if I use --> resampleColumns = "x", which is recommended in
the S-Plus Resample Help to use for Correlations, how should I exactly
understand this? -> Is there only the Column x permutated and the Column y left
behind?
iii) Most important question: Exists there another, better solution to do (1) to
(5)?
Please, can anybody help me.
Thank you!
Yours sincerly,
Weigl Klemens
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