Re: st: Analyzing a subpopulation in Stata 10.1

["Michael I. Lichter" <mlichter@buffalo.edu>]

Jeff,

It does make sense that the poststratification adjustment should be 
applied to the whole sample. The fact that the data is poststratified on 
nativity (which I purposely chose over sex, since there would have been 
no problem with female) means that the proportion female in the 
population is uncertain, which in turn means that the number of women 
who have ever born children should be that much more uncertain. I still 
have difficulty squaring the results from T3 from T4, since they are 
clearly contradictory and yet are *both* the result of "correct" 
adjustments of the survey weights.

Fortunately, I don't have any plans to report estimated counts in 
anything I'm working on right now; I'll just be sitting here worrying 
about whether my regressions, etc.., were performed with the correct 
weights.

In any event, I'll take a look at -svygen-.

Thanks again to you, and also to Figen.

Michael

Jeff Pitblado, StataCorp LP wrote:
> The thing to keep in mind here is that the poststratification adjustment must
> be applied to the entire estimation sample.
>
> It is not possible to reweight at the subpopulation level unless there is
> poststratification information at that level; i.e. if we had the postratum
> population sizes for the four cells defined by sex and native status.
>
> In table T3, -svy: tabulate- applies the weight adjustment to the 184
> observations in the estimation sample.  The only way to prevent that is to fix
> the adjusted weights ahead of time (see -help svygen-), but that isn't always
> a good solution.  The poststratified sampling weights are designed to reduce
> bias in the point estimates; however, with the postratum ID's -svy linearized-
> can produce more efficient variance estimates than without.
>
> Ultimately, it is the researcher/data-analyst that has the responsibility and
> power to choose which analysis is most appropriate for themselves.
>
> I can imagine real survey data where there are any number of different
> poststratification adjustments one could apply for a given analysis.  Some
> will make much more substantive sense than others.
>
> Suppose we had a variable called -ns_postid- that simultaneously identified
> the native status and sex of each individual in the dataset, and another
> variable called -ns_postw- that contained the population size for the
> corresponding group.  I think it is clear that this poststratification
> information could be applied more broadly than the one in Michael's simulate
> dataset.
>
> --Jeff
> jpitblado@stata.com
>
> PS.  There is an undocumented -svygen- command that will generate
> poststratification adjusted samling weights; see -help svygen-.
>
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--
Michael I. Lichter, Ph.D. <mlichter@buffalo.edu>
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

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