Re: st: using weights with -svy- commands

[Jeph Herrin <stata@spandrel.net>]

Thanks. To be clear: I am summarizing the data at the respondent level 
into something like a daily average. The exact algorithm for summation 
is rather complex (see http://www.ncbi.nlm.nih.gov/pubmed/18714120) but 
I would like to give more weight to respondents that have more days 
reported.

thanks,
Jeph


On 3/14/2012 12:49 PM, Stas Kolenikov wrote:
> [aweight] would have been called for if you summarized the 10k
> functional data points into a single number, an aggregate indicator of
> the level of physical activity. If you are analyzing all of the
> available motion data, I don't see any need to specify any additional
> weights. Depending on what exactly you are going to undertake in your
> analysis, you may or may not need the [pweights] or -svy- settings
> (and you can always compare the results using Hausman test, see
> Pfeffermann 1993
> http://www.citeulike.org/user/ctacmo/article/1036965).
>
> On Wed, Mar 14, 2012 at 11:48 AM, Jeph Herrin<stata@spandrel.net>  wrote:
> > All,
> >
> > This seems like a question that has been asked&  answered before, but I
> > can't find it in the archives.
> >
> > I have data which was was collected using a stratified survey design
> > (NHANES, http://www.cdc.gov/nchs/nhanes.htm) which I have been analyzing
> > using -svy- commands.
> >
> > However, for a random subset of survey respondents, additional data i
> > collected - up to 10080 motion counts collected each minute for up to 7
> > days. I have summarized these motion counts various ways for each
> > respondent, but since not all respondents have the same reporting period,
> > there is varying degrees of precision - some respondents have only a few
> > thousand counts, some have the full 10k - and most importantly, I have found
> > that the reporting period is associated with some of my key independent
> > variables (in particular, overweight children have shorter reporting periods
> > than normal weight children). So I want to incorporate the different
> > precision of the summary outcome into my regression models.
> >
> > In most linear regression models I would achieve this by weighting each
> > observation by the inverse of the variance of the dependent variable
> > measurement using -aweights-. However, -svy reg - does not support weights.
> >
> > My questions are all due to the fact that I am a casual user of complex
> > survey data. Is this because of a theoretical restriction due to the complex
> > designs? Or is it a mechanical problem that I can somehow circumvent? Or is
> > it possible with Stata, only I am overlooking the solution?
> >
> > thanks,
> > Jeph
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