I asked this question at BioStar but did not get a reply, so Im posting the question here.
What is a simple explanation of what an approximately unbiased bootstrap is with regards to hierarchical clustering?
From what I read, it alters the sample size during randomization to calculate p-values.
How is this approach better than the regular bootstrap which keeps the sample size intact while randomizing and also is it randomization with replacement?
Edit: There is an R package pvclust that calculates p-value and approximately unbiased p-value. My apologies for being unclear as I thought this was due to a difference in the bootstrap method. Thanks for all the answers and comments!