The formula in the archive is not OK for all purposes. The weights
computed by it will not sum to population totals and will not equal
the weights produced by Stata.
For a simple random sample, the post-stratified weight for an
observation in post-straum h is : N_h divided by n_h where N_h is
the population total in the stratum and n_h is the sample number in
the post-stratum. You should prove the formula from the section on
post-stratification in one of your sampling books or in the Stata
manual. I would certainly not regard my post here as authoritative
enough to serve as a publication reference.
Note that if your colleagues treat the post-stratification weights as
ordinary pweights, they might not get the same standard errors as
Stata does.
I'm going to quote Mike Hanson's instructions to his advanced
econometrics class again:
"Never push a button or type a command you do not fully understand.“
(Statalist May 8, 2009)
-Steve
On Mon, Sep 21, 2009 at 2:45 PM, Michael I. Lichter
<[email protected]> wrote:
> Carolina,
>
> I didn't look very closely at the e-mail in the archive, but it seems OK. It
> would be easier, however, to use the undocumented -svygen poststratify-
> command in Stata 10 and 11 or the user-written -survwgt- package ("findit
> survwgt") (which also does raking and is a bit more flexible if also more
> complex).
>
> Note that if you use a sub-package that supports pweights, like the SPSS
> complex samples (CS*) routines, you should get the same results as in Stata
> if your tabulations are for the whole sample. For subsamples, results may
> differ because Stata svy poststratification will adjust the weights for the
> subsetting in a way that the other package will not.
>
> -----
> sysuse auto
> gen count = 100 if foreign ==0
> replace count = 120 if foreign == 1
> svyset, poststrata(foreign) postweight(count)
> svy: tab foreign, count
> svygen poststratify pswt, poststrata(foreign) postweight(count)
> svyset [pw=pswt]
> svy: tab foreign, count
> -----
>
> Michael
>
> Carolina Herrera wrote:
>>
>> Hello everyone,
>> I am working with a very simple random sample that we've post-stratified
>> using the standard commands in Stata (poststrata postweight fpc). A
>> colleague would also like to use the dataset, but he doesn't work in Stata
>> and wanted a version that could be used in any other statistical package
>> (SPSS, SAS, R, etc.).
>>
>> After hunting around on the statalist archives I found a post explaining
>> how to manually calculate post-stratification weights:
>> (http://www.stata.com/statalist/archive/2008-11/msg00152.html) which, I
>> think suggested I treat these post-stratification weights like pweights and
>> that these pweights could then be implemented in Stata (or elsewhere) to get
>> the same point-estimators and standard errors.
>> Is that the correct way to implement simple post-stratification without
>> using Stata's post-stratification commands?
>>
>> many thanks, Carolina
>>
>>
>> Carolina Herrera
>> Statistician
>> Center for the Health Professions
>> UCSF
>>
>
> --
> Michael I. Lichter, Ph.D. <[email protected]>
> Research Assistant Professor & NRSA Fellow
> UB Department of Family Medicine / Primary Care Research Institute
> UB Clinical Center, 462 Grider Street, Buffalo, NY 14215
> Office: CC 126 / Phone: 716-898-4751 / FAX: 716-898-3536
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
--
Steven Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
845-246-0774
*
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