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Re: st: random subsample - sample weights

From   "Austin Nichols" <>
Subject   Re: st: random subsample - sample weights
Date   Thu, 15 Feb 2007 12:33:59 -0500

Ellen and Stas--
The Fairlie decomposition alluded to is implemented without weights in
the SSC package -fairlie- (references are in the help file), and
depends not only the specifics of the match but on the order of
variables used to match!
Fairlie uses the delta method to approximate std errors, but it's not
clear that its use is justified in this case of one-to-one matching.

In any case, you may want to take Ben Jann's -fairlie- command as a
starting point, or you may prefer to investigate the alternative due
to Yun:
and many other related papers available via a web search.

On 2/15/07, Stas Kolenikov <> wrote:
There is a bunch of different implementations of probability
proportional to size (PPS) sampling floating around

On 2/15/07, Ellen Van de Poel <> wrote:
> I want to draw a random subsample from my data, but taking into account my
> sample weights.
> I thought of inflating my data (with the command "expand") to get rid of the
> weights and then draw a random subsample from the expanded data. But I'm not
> sure whether this is correct, since then I can have the same observation
> multiple times in the random subsample?
> Thereafter I match this random subsample with another sample (I'm doing a
> Fairlie decomposition). So I guess it is necessary to account for the sample
> weights when I match the random subsample with another sample?
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