James <[email protected]> :
Here's what I would do:
egen c=group(stata psu), m
ologit depvar indvar1 indvar2 [pw=pw], cluster(c).
which puts all the missing-strata people in one stratum.
On Fri, Aug 28, 2009 at 11:59 AM, Sanders, James Parry<[email protected]> wrote:
> Hello,
> NELS (educational) data comes packaged with psu, pw, and strata data. When I svyset the data, I am told that 1,406 cases have missing values in the survey characteristics (all 1,406 are missing psu and strata data). Thus, when I run a survey command (e.g. svy: ologit) these 1,406 are excluded from the analysis. Alternatively, I can keep the 1,406 in by running a standard command and including 2 of the three weights but leaving out the strata values (e.g. ologit depvar indvar1 indvar2 [pw=pw], cluster(psu)). Either way the results are essentially the same.
>
> My question(s) is/are this: Which way is preferred? The first way includes all weights but drops 8% of the sample who otherwise have complete data. The second way keeps everyone but doesn't include the strata data and may thus not be fully representative of the population. Is there a way to keep cases lacking psu and strata data in svy commands. Alternatively, is there a way to include the strata data in the non-survey command?
> Thanks for any help,
> James
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