That's terrible -- they have a 100k input file with 2200+ lines, but
did not bother to put just one more line for the appropriate design
specification!
Here's my understanding of NHIS: the household was conducted, and data
were collected for each person (by self or proxy reporting) producing
the person file. The weights in the person file would essentially be
the household weights. An adult was sampled to provide more detailed
information; their weight will be higher than the person weight by the
factor equal to (# of people in the household). All sampled adults
should have reported on the cancer supplement, so the sample adult and
the sample adult cancer data should have the same weights.
What was it that you tried to achieve by merging the three files? My
understanding is that you should've received almost a block-diagonal
structure of your data: the variables from the person data go with the
person(=household) weights, the variables from the sample adult and
cancer data go with the sample adult weights, and the
observations/variables do not overlap. Am I wrong? If you want to mix
information from them in your analysis, then you will have a lot of
missing data from the unsampled adults who did not provide the
information for the sample and cancer data sets. If only do the
analysis using the person data, you should use the wtfa weights from
the person data. If your analysis uses sample adult and cancer data,
you should use wtfa_sa weights. I expect that it will be impossible to
meaningfully analyze the data from all three files simultaneously, but
I will likely be wrong with this.
On Mon, Jul 20, 2009 at 11:07 AM, Michael
Drazer<[email protected]> wrote:
> Hello,
>
> I am new to STATA and am doing some work with a dataset that I created by
> merging together the 2005 sample adult, person, and sample adult cancer NHIS
> datasets. I'm trying to construct an appropriate survey design statement,
> but am not sure how to properly define the pweights for my dataset.
>
> According to the Sample Adult variable layout, the wtfa_sa weight should be
> used for most sample adult analyses - I noticed, however, that the Sample
> Adult dataset also has values for the wtfa weight. All of the 98,649
> observations in my merged dataset have wtfa weights, but only those 31,428
> observations in the sample adult/sample adult cancer datasets contain
> wtfa_sa weights. My question is: to properly weigh this data, should I use a
> standard survey design statement, such as:
>
> svyset [pweight=wtfa],strata(stratum)psu(psu)
>
> even though it does not take into account the wtfa_sa weights, or is there a
> better way to weigh this data?
>
> For additional info re: variable layouts in the NHIS data, see here (the
> Variable layout PDFs are informative in terms of a description of the wtfa
> and wtfa_sa variables - see the person layout for wtfa and either the sample
> adult or sample adult cancer layout for the wtfa_sa variable):
> http://www.cdc.gov/nchs/nhis/nhis_2005_data_release.htm
>
> Thanks in advance,
>
> Michael
>
>
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--
Stas Kolenikov, also found at http://stas.kolenikov.name
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