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Re: st: Bootstrapping weighted glm regression
From
Austin Nichols <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: Bootstrapping weighted glm regression
Date
Wed, 21 Aug 2013 09:48:53 -0400
Stephen Amrock <[email protected]>:
Wrap the whole thing, propensity score estimation and weight
generation and -glm-, inside one -program- and bootstrap the new
program. You can also roll your own bootstrap using -bsample- and
-bstat-. Are you sure you want a log link--is that a binary outcome?
On Wed, Aug 21, 2013 at 9:07 AM, Stephen Amrock
<[email protected]> wrote:
> Hi,
>
> I'm conducting survival analysis using inverse probability weighting
> (IPW) (i.e., stabilized weights generated from propensity scores). I'm
> hopeful someone will be able to help with some guidance regarding
> Stata's (1) weighting; and (2) bootstrap features. It appears that
> bootstrap never can work with weighted data. Is there a workaround for
> this?
>
> Stata, for example, can compute:
>
> glm [outcome] [treatment], family(binomial) link(log) eform vce(boot,
> r(1000) nodots)
>
> but can NOT perform bootstrapping for the following:
>
> glm [outcome] [treatment] [pw=weight], family(binomial) link(log)
> eform vce(boot, r(1000) nodots)
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