Margo Schlanger<[email protected]> :
I think Michael I. Lichter means for you to -append- your sample and
population in step 2 below. Then you can run -hotelling- or the
equivalent linear discriminant model (with robust SEs) to compare
means for a bunch of variables observed in both. I.e.
. reg sample x* [pw=wt]
in step 2b, not tabulate, with or without svy: and chi2.
On Fri, Jul 24, 2009 at 11:24 PM, Michael I.
Lichter<[email protected]> wrote:
> Margo,
>
> 1. select your sample and save it in a new dataset, and then in the new
> dataset:
> a. define your stratum variable -stratavar- as you described
> b. define your pweight as you described, wt = 1/(sampling fraction) for each
> stratum
> 2. combine the full original dataset with the new one, but with stratavar =
> 1 for the new dataset and wt = 1 and with a new variable sample = 0 for the
> original and =1 for the sample, and then
> a. -svyset [pw=wt], strata(stratavar)-
> b. do your chi square test or whatever using svy commands, e.g., -svy: tab
> var1 sample-
>
> Michael
>
> Margo Schlanger wrote:
>>
>> Hi --
>>
>> I have a dataset in which the observation is a "case". I started with
>> a complete census of the ~4000 relevant cases; each of them gets a
>> line in my dataset. I have data filling a few variables about each of
>> them. (When they were filed, where they were filed, the type of
>> outcome, etc.)
>>
>> I randomly sampled them using 3 strata (for one strata, the sampling
>> probability was 1, for another about .5, and for a third, about .75).
>> I end up with a sample of about 2000. I know much more about this
>> sample.
>>
>> Ok, my question:
>>
>> 1) How do I use the svyset command to describe this dataset? It would
>> be easy if I just dropped all the non-sampled observations, but I
>> don't want to do that, because of question 2:
>>
>> 2) How do I compare something about the sample to the entire
>> population, just to demonstrate that my sample isn't very different
>> from that entire population on any of the few variables I actually
>> have comprehensive data about. I could do this simply, if I didn't
>> have to worry about weighting:
>>
>> tabulate year sample, chi2
>>
>> But I need the weights. In addition, I can't simply use weighting
>> commands, because in the population (when sample == 0), everything
>> should be weighted the same; the weights apply only to my sample (when
>> sample == 1). And I can't (so far) use survey commands, because I
>> don't know the answer to (1), above.
>>
>> NOTE: Nearly all the variables I care about are categorical: year of
>> filing, type of case. But it's easy enough to turn them into dummies,
>> if that's useful.
>>
>>
>> Thanks for any help with this.
>>
>> Margo Schlanger
>>
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