Hi: I am new to the list and have a question about bootstrap hypothesis testing. I am
testing the equality of two means according to Algorithm 16.2 in An Introduction to
the Bootstrap by Efron and Tibshirani (1993). They define the estimated ASL as
#{t(x*b) >= tobs}/B. It seems to me that this is a one sided estimated ASL. I can
easily determine the significance or lack or significance by changing the order of the
means I subtract.
My question is why is the ASL defined as >=? Why would I not wish to examine both ends
of the null distribution?
Thanks for your help.
Joe
Joe Horton
Psychology and Social Sciences Department
7373 Admiral Peary Highway
Mount Aloysius College
Cresson, PA 16630
(814) 886-6437
[EMAIL PROTECTED]
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