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Re: st: bootstrap weights


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
Subject   Re: st: bootstrap weights
Date   Fri, 25 Nov 2011 21:29:51 -0500

Yes, I figured as much... guess I just liked the way it sounded. :)

> Date: Fri, 25 Nov 2011 18:55:53 -0600
> Subject: Re: st: bootstrap weights
> From: skolenik@gmail.com
> To: statalist@hsphsun2.harvard.edu
> 
> Cam,
> 
> that's an overkill. You are trying to outsmart the data by being to
> conservative.
> 
> Stefano,
> 
> that's probably the best you can do. I would suggest using more
> replications (reps() option) and fewer subsampled units (I tend to use
> n(-1), although with several thousand observations that you probably
> have, the small sample performance these adjustments tend to improve
> does not matter). Ask your data providers if they can generate the
> bootstrap weights on their side using their strata information.
> 
> On Fri, Nov 25, 2011 at 3:32 PM, Cameron McIntosh <cnm100@hotmail.com> wrote:
> > Stefano,
> >
> > I wonder if another, conservative approach might be to form clusters that maximize ICC, or more directly the intra-cluster covariances of the parameter estimates, and then use Taylor linearization to get your adjusted standard errors. It may take a bit of work to write an algorithm to generate clusters such as I describe.
> >
> > For what it's worth,
> >
> > Cam
> >
> >> Date: Fri, 25 Nov 2011 19:39:43 +0000
> >> Subject: Re: st: bootstrap weights
> >> From: verdes@tcd.ie
> >> To: statalist@hsphsun2.harvard.edu
> >>
> >> Dear Bryan and Steven,
> >>
> >> thank you very much for your help.
> >>
> >> Only today the national statistics office confirmed to me that: 1) no
> >> clusters were used in the household survey I have, and 2) they cannot
> >> release information about strata.
> >> Thus, my microdata set only includes sampling weights (which sum up to
> >> Ireland's household population, N).
> >>
> >> Given this, what is the best I can do? I have thought of the following:
> >>
> >> svyset _n [pw = my_sampling_weights]
> >> bsweights bsw, n(0) reps(100)
> >> bs4rw exp_list, rw(bsw*): command [pw = my_sampling_weights]
> >>
> >> The first line - on Steven's suggestion - states that there is a
> >> single stratum only and each household is a PSU.
> >> The second line creates bootstrap resampling weights, which are then
> >> used in the bootstrap of exp_list (-bsweights- and -bs4rw- are
> >> commands written by Stas Kolenikov).
> >>
> >> I'm aware that not having information on strata affects results.
> >> However, my two questions are:
> >>
> >> 1) Do sampling weights mitigate this error?
> >>
> >> 2) Are the three command lines above the best I can do, given the
> >> information limitations?
> >>
> >> Once again I'd greatly appreciate your help.
> >>
> >> Best regards,
> >> Stefano Verde
> >>
> >> *
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> >
> >
> > *
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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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