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Re: st: using weights with -svy- commands


From   Stas Kolenikov <[email protected]>
To   [email protected]
Subject   Re: st: using weights with -svy- commands
Date   Wed, 14 Mar 2012 12:49:15 -0400

[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 <[email protected]> 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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-- 
Stas Kolenikov, also found at http://stas.kolenikov.name
Small print: I use this email account for mailing lists only.

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