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Re: st: RE: Weighting in -xtprobit-


From   "Clive Nicholas" <Clive.Nicholas@newcastle.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Weighting in -xtprobit-
Date   Mon, 10 Nov 2003 14:47:07 -0000 (GMT)

Steve,

Will certainly take that advice on iweights: thanks! :-) I've just seen a
post by Jane Bruce which demonstrates that you can use pweights for
-xtlogit- models, so I'm going to see if I can do the same for -xtprobit-
(since, for some odd reason, I can't run -xtlogit- models despite the fact
that I have fixed effects in the form of regional residence in my models).
Thanks once again.

C.

> Clive,
> A few points here:  (1) stay away from iweights -- in general, they have
> no
> statistical meaning in stata and exist as a way for programmers to modify
> an
> estimator in a particular way, (2) pweights are the appropriate weight for
> sampling issues -- as is often the case with more complicated regression
> models, my guess is that the estimator for a random effects probit model
> with sampling weights has never been derived, (3) if you control for all
> variables that are used to determine your sample weights (and these are
> exogenous to your outcome variables) and cluster on households (or PSUs,
> if
> available), your results will be asymptotically equivalent to an estimator
> that takes sampling weights directly into account.
>
> Steve
>
> -----Original Message-----
> From: Clive Nicholas [mailto:Clive.Nicholas@newcastle.ac.uk]
> Sent: Saturday, 8 November 2003 8:48
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Weighting in -xtprobit-
>
>
> All,
>
> OK, yet another question I wished to ask the list that I'll probably get
> flamed for, but I think it's interesting (and essential for me to fix).
>
> I've recently fitted some -xtprobit- models quite recently. It took time,
> but bar one exception, all the models ran with decent results. As a new
> Statabod, I was rather pleased with myself (not that that's ever too
> difficult). Then I realised something: since this was panel survey data I
> was using, I didn't weight the analysis!! :((
>
> I had to start over trying to use Stata's weights. Unfortunately, it won't
> run [pw=...], [aw=...] or [fw=...]. It ran [iw=...), but it returned a
> model
> full of low coefficents and highly insignificant p-values. Given that the
> data was sampled from households at random, [aw] and [fw] do not appear to
> be appropriate (certainly going by their descriptions in [U], 23.16.
> Option
> [pw] looks to be the most appropriate, but Stata returns the error:
> "pweight
> not allowed in random-effects case r(101);".
>
> It's been suggested to me that, instead, I may be able to reduce the
> effect
> by entering the number of adults in household, age and marital status and
> other such variables in the model. This is because Scottish households
> were
> oversampled and that people in small households have a much larger chance
> of
> selection than people in large households in this British survey (e.g. a
> person in a one adult household has twice the selection chance of a person
> in a two adult household). I've entered the last two of these in my
> models,
> but not the first (yet).
>
> So to bring this mini-epic to its cliffhanger, could adding such variables
> get round the problem of not being able to formally use -[pw=(weight)]- in
> -xtprobit-? Or are there other automatic fixes?
>
> Thanks in advance. :)
>
> Yours,
> CLIVE NICHOLAS,
> Politics Building,
> School of Geography, Politics and Sociology,
> University of Newcastle-upon-Tyne,
> Newcastle-upon-Tyne,
> NE1 7RU,
> United Kingdom.
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Yours,
CLIVE NICHOLAS,
Politics Building,
School of Geography, Politics and Sociology,
University of Newcastle-upon-Tyne,
Newcastle-upon-Tyne,
NE1 7RU,
United Kingdom.
*
*   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/



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