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RE: st: how to weight


From   Richard Williams <Richard.A.Williams.5@nd.edu>
To   statalist@hsphsun2.harvard.edu, <statalist@hsphsun2.harvard.edu>
Subject   RE: st: how to weight
Date   Wed, 10 Mar 2004 18:40:01 -0500

At 11:07 PM 3/10/2004 +0000, Nick Cox wrote:
As you say, non-integers cannot be frequency weights.

Otherwise how these weights are to be interpreted looks like
a substantive matter. You need to move upstream
towards the author or supplier of the dataset.
Agreed. If the authors have provided weights, they've also hopefully provided information on how to use them. It might also be that, instead of just using the weights, you want to use Stata's svy commands (e.g. clustering and/or stratification may have been used when gathering the data, and if so variables that indicate that are also hopefully included.)

I would also highly recommend getting the Stata 8 User's Guide and going over sections 23.14 (Robust variance estimates) and 23.16 (weighted estimation). These have the best explanations I have seen of Stata's weighting procedures (does anyone know of anything on the web that comes close to providing an adequate explanation?). Depending on the data, you may also want the survey data manual.

The main (only?) difference between pweights and aweights that I am aware of is that pweights forces the use of robust standard errors, i.e. parameter estimates are not changed but standard errors are. SPSS, as far as I know, does not provide an easy means of getting the robust standard errors, which I would say is one of SPSS's weaknesses.

If analyses have already been done in SPSS using the weight command, my wild guess is that you will get the same results by using aweights in Stata. But, my wild guess is also that, either way, the results will be wrong; the Stata Users guide has a good explanation of how aweights have been, and continue to be, used improperly. If I had to bet, I would bet on pweights being best. But again, you really need to know more about the data before you can decide on how to proceed.


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Richard Williams, Notre Dame Dept of Sociology
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