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Re: st: pweight question

From   Steve Samuels <>
Subject   Re: st: pweight question
Date   Thu, 29 Apr 2010 20:37:12 -0400

I have other problems with these scaled weights.

First, if they are all you have, it is difficult to  identify  weights
that  are too  small. (Ken Brewer, Combined Survey Sampling Inference,
Wiley, p. 133).

Second, with these scaled weights one cannot recover the original ones
without information on the total, and the information is not always
available. In fact, for some samples, the population total isn't known
and the only estimate is based on the original probability weights.

Third, I wonder about the accuracy of the scaled weights.  If n is
moderate and  the sampling fraction is small, most of the significant
figures could be far to the right of the decimal place.

Finally, these weights just lead to confusion on the part of people
who were not in on their construction. The original poster was
confused on this occasion, and I was confused on another last year.


On Thu, Apr 29, 2010 at 5:47 PM, Stas Kolenikov <> wrote:
> On Thu, Apr 29, 2010 at 3:03 PM, Michael I. Lichter
> <> wrote:
>> The scale of the weights (what they sum to) doesn't tell you whether or not
>> they are pweights.
> That's not quite right. Properly scaled probability weights should sum
> up to the population size. This however is only relevant when you
> estimate -total-s. If you run pretty much any other analysis (means,
> ratios, proportions, any sort of regressions), then the scale of the
> weights cancels out. I would grind my teeth at the pweights that are
> scaled to the sample size, and maybe make some mental comments about
> the data provider, but won't be bothered very much by this nuisance.
> The scaling of the weights begins to matter again with multilevel
> data, in which the scaling is known to affect the accuracy of the
> variance component estimates.
> --

Steven Samuels
18 Cantine's Island
Saugerties NY 12477
Voice: 845-246-0774
Fax: 206-202-4783
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