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Re: st: Applying specific aweight to each explanatory variable
From
Austin Nichols <[email protected]>
To
[email protected]
Subject
Re: st: Applying specific aweight to each explanatory variable
Date
Thu, 10 Nov 2011 13:35:35 -0500
Natacha <[email protected]>:
The request makes little sense as stated, but perhaps you have in mind
that individual observations on individual variables are measured with
error of (known) different variance, and you want to shrink
observations toward some group mean. You could in theory adapt the
root-N factors in the aweight example in the Technical Note on page
1530 of the manual entry for -regress-, but it makes more sense to
mechanically shrink each value toward zero or toward some group mean
using an empirical Bayes shrinkage technique. Without a reference
supporting the approach, you will probably have to marshal some
simulation evidence to show this improves over weights that multiply
all variable-specific weights together to get an observation-level
average precision aweight, or an approach that ignores all aweights.
On Thu, Nov 10, 2011 at 9:01 AM, <[email protected]> wrote:
> Hi All,
>
> I'm running simple cross-sectional regressions. I would like to know whether it is possible to make Stata apply a different aweight to each separate explanatory variable.
>
> Usually at the end of the regression I can just write [aweight = exp], but this would apply the same aweight to each explanatory variable. I would like to know whether it's possible to specify a different exp as an aweight for each different explanatory variable, and whether that would make any sense or not.
>
> Many thanks,
>
> Natacha
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