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st: RE: bootstrapping survey data
The rationale for bootstrapping my coefficient
estimates is to include some sense of the uncertainty
of the parameters in a Monte Carlo simulation of the
effect of a policy change. For the first order Monte
Carlo simulation I am taking draws from a conditional
distribution defined by the logit model I estimate
using the NHIS. A second order Monte Carlo analysis
reruns this simulation some large number of times,
each time using a conditional distribution defined by
the parameter estimates from one of the bootstrap
draws. Thus, the error from the parameter estimates is
taken into account in my simulation results.
All of that said, bootstrapping assumes that the
empirical distribution of the sample is a reasonable
approximation of the actual distribution in the
population. In order to have the resamples mimic the
initial sample, I would like to take account of the
sampling design, to the extent that it is known to me.
While I don't have exact knowledge of the sampling
design, it is my sense that for the purposes of making
my simulation plausible, I should include what
elements of the sampling design I can. Thus, my
interest in bootstrapping my estimates from the NHIS.
I welcome any opinions on either my analysis strategy
in general or the Stata problem in particular.
--- "Sayer, Bryan" <BSayer@s-3.com> wrote:
> I don't understand the point of doing both a
> bootstrap and explicitly
> accounting for the sample design (I'm presuming you
> set PSU and strata since
> you specified svylogit).
> Anyway, bootstrapping of complex survey design data
> is not especially well
> developed, outside of replication weights.
> Generally, setting up the
> process requires knowledge of the sampling variables
> that might not be
> NHIS is properly handled in Stata simply by setting
> PSU, strata and pweight
> (absent a very small subpop).
> Bryan Sayer
> Statistician, SSS Inc.
> -----Original Message-----
> From: doug levy
> To: email@example.com
> Sent: 7/10/03 4:40 PM
> Subject: st: bootstrapping survey data
> Dear Statalisters,
> I am trying to get bootstrapped estimates of
> coefficients from a complex survey (the National
> Health Interview Survey). To get standard estimates,
> would type "svylogit Y X" after having set up the
> weights, strata, and psu's. To get bootstrap
> estimates, my first inclination was to run
> "logit Y X [pw=weight]" _b, reps(1000)
> psu(psu)'. However, Stata does not allow weights in
> bootstrap. I was able to trick Stata into including
> weights by using only the weights in the svyset
> command and running 'bootstrap "svylogit Y X" _b,
> reps(1000) strata(stratum) psu(psu)'. This gives me
> point estimates similar to the non-bootstrapped
> estimates, which is reassuring, but will I get
> reasonable standard errors? Is there a more orthodox
> way of coding this?
> Many thanks for any and all advice,
> Doug Levy
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