On 3/25/07, James Shaw <ximon1@hotmail.com> wrote:

Thank you for your response. I will take a look at the papers you
suggested. I have read several papers discussing variants of the jackknife
designed for handling WOR sampling and/or unequal selection probabilities.
Most notably:
Berger YG, Skinner CJ. A jackknife variance estimator for unequal
probability sampling. J R Statist Soc B 2005; 67(Part 1): 79-89.

I am not familiar with that one -- will look it up. I think the
overall agreement has been that all of the resampling methods are best
implemented through the method of weights --
http://www.citeulike.org/user/ctacmo/article/1036966. It is pretty
much impossible to get electronically, so I can send you a copy. If
you do this literally by resampling, then those methods may not indeed
by directly applicable. What Rao, Wu and Yue suggseted is to view all
of the resampling problems as applying different weights, and
demonstrate how those weights can be derived. I think this is what you
are asking below as well --

One further question. If the jackknife were appropriate for use with
unequal probability sampling at the first stage, then would this not imply
that the bootstrap could be used instead? I assume that the sampling
weights would need to be suitably rescaled for each replicate sample.

--
Stas Kolenikov
http://stas.kolenikov.name
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