*I asked [this question at BioStar](http://www.biostars.org/post/show/48338/approximately-unbiased-bootstrap-vs-bootstrap/) 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!