Stas wrote:
I think the best idea with the bootstrap in complex surveys is to
relegate everything to the weights and modifications of those, as
described in Rao, Wu and Yue (1992) paper that I can send.
I'd love to see that, if you don't mind. Thanks.
Doing the stuff properly with -pweights- would require something like
PPS sampling, which is another disaster in the survey statistics world
-- it is far more computationally intensive than it might seem.
This is what confuses me. When working on -kdens- I did some
simulations to compare the bootstrap CI's with the normal theory CI's
in the presence of -pweights-. I was convinced that I had to implement
PPS sampling for the bootstrap to be accurate. However, the results
were as follows:
- bootstrap with PPS sampling (and leaving away the weights within the
bootstrap samples) produced CI's that were like those obtained form
normal theory formulas with -aweights-(!)
- bootstrap with simple random sampling (and applying the weights
within the bootstrap samples) produced CI's that were like those
obtained form normal theory formulas with -pweights-
Well, I don't know. Hm ...
ben
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