R help - Aug 2008 - Quantile regression with complex survey data

Dear there,

I am working on the NHANES survey data, and want to apply quantile
regression on these complex survey data. Does anyone know how to do
this?

Thank you in advance,
Yiling Cheng
Yiling J. Cheng MD, PhD
Epidemiologist
CoCHP, Division of Diabetes Translation
Centers for Disease Control and Prevention
4770 Buford Highway, N.E. Mailstop K-10
Atlanta, GA 30341
 



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> Dear there,
> 
> I am working on the NHANES survey data, and want to apply quantile
> regression on these complex survey data. Does anyone know how to do
> this?
> 
> Thank you in advance,
> Yiling Cheng
> Yiling J. Cheng MD, PhD
> Epidemiologist
> CoCHP, Division of Diabetes Translation
> Centers for Disease Control and Prevention
> 4770 Buford Highway, N.E. Mailstop K-10
> Atlanta, GA 30341
>  
> 
> 
	[[alternative HTML version deleted]]

On Wed, Aug 20, 2008 at 8:12 AM, Cheng, Yiling (CDC/CCHP/NCCDPHP)
<ycc1 at cdc.gov> wrote:
> I am working on the NHANES survey data, and want to apply quantile
> regression on these complex survey data. Does anyone know how to do
> this?
There are no references in technical literature (thinking, Annals,
JASA, JRSS B, Survey Methodology). Absolutely none. Zero. You might be
able to apply the procedure mechanically and then adjust the standard
errors, but God only knows what the population equivalent is of
whatever that model estimates. If there is a population analogue at
all.

In general, a quantile regression is a heavily model based concept:
for each value of the explanatory variables, there is a well defined
distribution of the response, and quantile regression puts additional
structure on it -- linearity of quantiles wrt to some explanatory
variables. That does not mesh well with the design paradigm according
to which the survey estimation is usually conducted. With the latter,
the finite population and characteristics of every unit are assumed
fixed, and randomness comes only from the sampling procedure. Within
that paradigm, you can define the marginal distribution of the
response (or any other) variable, but the conditional distributions
may simply be unavailable because there are no units in the population
satisfying the conditions.

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