Von: gregor rolshausen <gregor.rolshausen at biologie.uni-freiburg.de>
Betreff: Re: [R] How to compute p-Values
An: "r help" <r-help at r-project.org>
Datum: Mittwoch, 14. Januar 2009, 11:31
Andreas Klein wrote:
Hello.
How can I compute the Bootstrap p-Value for a one- and
two sided test, when I have a bootstrap sample of a
statistic of 1000 for example?
My hypothesis are for example:
1. Two-Sided: H0: mean=0 vs. H1: mean!=0
2. One Sided: H0: mean>=0 vs. H1: mean<0
hi,
do you want to test your original t.test against t.tests of
bootstrapped samples from you data?
if so, you can just write a function creating a vector with
the statistics (t) of the single t.tests (in your case 1000
t.tests each with a bootstrapped sample of your original
data -> 1000 simulated t-values).
you extract them by:
tvalue=t.test(a~factor)$statistic
then just calculate the proportion of t-values from you
bootstrapped tests that are bigger than your original
t-value.
p=sum(simualted_tvalue>original_tvalue)/1000
(or did I get the question wrong?)
cheers,
gregor