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From |
Mohammed El Faramawi <melfaram@yahoo.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: median regressin and survey data! |

Date |
Mon, 31 Mar 2008 13:20:28 -0700 (PDT) |

I appreciate it Austin. Your answer is very convincing Mohammed faramawi, MD,PhD,Msc,MPH --- Austin Nichols <austinnichols@gmail.com> 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 > <skolenik@gmail.com> 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 > <melfaram@yahoo.com> 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 > * > * For searches and help try: > * > http://www.stata.com/support/faqs/res/findit.html > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ > ____________________________________________________________________________________ No Cost - Get a month of Blockbuster Total Access now. Sweet deal for Yahoo! users and friends. http://tc.deals.yahoo.com/tc/blockbuster/text1.com * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: median regressin and survey data!***From:*"Austin Nichols" <austinnichols@gmail.com>

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