I appreciate it Austin. Your answer is very convincing
Mohammed faramawi, MD,PhD,Msc,MPH
--- Austin Nichols <[email protected]> wrote:
> Another short answer:
>
http://www.stata.com/statalist/archive/2007-09/msg00147.html
>
> and long answer:
> Even the -svy- commands do not give you the test you
> often want, for
> whether the means/medians/etc. are the same for two
> data generating
> processes (say, men and women) or the
> means/medians/etc. of the
> distributions in some superpopulation of possible
> populations are
> equal. For an unstratified survey sample, you can
> usually just account
> for clustering (on PSU) and weights and ignore the
> fpc and get the
> right answer, but for stratified samples, a
> theoretically justifiable
> test may not be programmed. However, using weights
> (either as
> aweights or pweights) and bootstrapping with the
> cluster option will
> often give accurate inference when your options are
> limited. There is
> also a strata option for bootstrap, but
> weights+cluster may get you
> the best performance--in the absence of a proof, you
> can always run
> some simulations to convince yourself it will work
> for your particular
> problem (by generating datasets that look more or
> less like yours).
>
>
> On Sat, Mar 29, 2008 at 12:15 PM, Stas Kolenikov
> <[email protected]> wrote:
> > Short answer: neither one fits well enough into
> the paradigm of survey
> > sampling, so coming up with fully justifiable
> implementation is not
> > straightforward.
> >
> > Long answer.
> >
> > For the first one, all rank tests implicitly
> assume the data are
> > i.i.d., and I don't think very clear analogies
> are possible with
> > survey data. There are no estimating equations to
> work with; you
> > probably would be able to get the distribution of
> the test statistic
> > over repeated sampling, but it won't be nearly as
> nice as the textbook
> > distribution.
> >
> > For the second one, -qreg-is a heavily
> model-based concept: that for
> > any combination of explanatory variables, there's
> a well defined
> > distribution of responses over which the median
> can be computed. The
> > straight design perspective, on the other hand,
> says that there are
> > only so many individuals in the finite
> population, so there is no talk
> > about conditional distributions. So one needs to
> invent some sort of a
> > hybrid framework to incorporate both model and
> design ideas, and they
> > don't always go hand in hand. A basic
> introduction to the subject is a
> > chapter by Binder and Roberts in 2003 Analysis of
> Survey Data book
> > (http://doi.wiley.com/10.1002/0470867205.ch3) --
> I say introductory
> > because they consider the simplest possible
> situations, but they still
> > operate with big-O small-O in probability.
> Conceptually, it should
> > still be possible to formulate median regression
> for sample surveys,
> > as it is linked to a minimization problem, and
> thus can be cast in
> > terms of estimating equations. Then you need to
> say, "If I had the
> > full population, I would run this same median
> regression on it, and
> > get some numbers from this census estimation
> procedure. Now, what I
> > can hope for with the sample is that my estimates
> are going to be
> > consistent for those numbers that came out of the
> census problem". I
> > don't really know if that was done for quantile
> regression; for linear
> > regression, the comparable result goes back to
> mid 1970s due to Wayne
> > Fuller, and for generalized linear models, to
> David Binder's 1983
> > paper. Median regression is somewhat trickier
> though, as the function
> > being minimzed, the sum of absolute deviations,
> is not differentiable,
> > so the standard tools like the delta method are
> not applicable.
> >
> >
> >
> > On 3/29/08, Mohammed El Faramawi
> <[email protected]> wrote:
> > > Hi,
> > > I am trying to run non-parametric tests using
> survey
> > > data ( probability weighted). unfortunately I
> can not
> > > find commands which takes into the
> consideration the
> > > pweight. I am interested in qreg (median
> regression)
> > > and Mann-Whitney test. Is there any way to do
> this by
> > > Stata? Thank you
> > > Mohammed Faramawi, MD,Phd,MPH,Msc
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