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Re: st: Re: propensity score


From   Zeynal Karaca <zeynalkaraca@gmail.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Re: propensity score
Date   Wed, 1 Jun 2011 13:01:52 -0400

Thanks for the follow-ups. I believe I got the answers for my simple research question when utilizing Stata. Thanks again...

Zeynal Karaca, PhD

On Jun 1, 2011, at 11:01 AM, "Ariel Linden. DrPH" <ariel.linden@gmail.com> wrote:

> The questions you are asking are basic to the design and structure of
> propensity score matching. As a Stata list-serve, we mostly deal with issues
> related to implementation of statistics in Stata and mostly assume the
> person querying the list-serve has a grasp of the subject matter.
> 
> There are numerous papers and books on the topic of conducting a study using
> propensity scored matching techniques. If you can't find them on your own,
> we can certainly point you in that direction.
> 
> Ariel
> 
> Date: Tue, 31 May 2011 06:29:50 -0400
> From: zeynal karaca <zeynalkaraca@gmail.com>
> Subject: Re: st: Re: propensity score
> 
> While digesting different component of propensity ADO codes, here is
> another question on the same subject for which any help is
> appreciated:
> 
> The research question I am working on is to tease out the differences
> in treatment costs between two different insurance holders, say
> Insurance A and Insurance B. I am using an administrative data for
> this purpose. The process I am running is to select a set of Insurance
> A beneficiaries for whom I can get a match from Insurance B
> beneficiaries based on observed characteristics, call X1 and X2.
> 
> In the first stage, I am running a logit regression to determine
> probability of choosing insurance A using X1 and X2 and get the
> predicted probability, call Phat. In the second stage, GLS regression,
> I am regressing the cost per beneficiaries on X2, X3 and Phat assuming
> that the Phat will capture the differences in costs controlling for
> other factors. So the naive question I have here is about X2, which
> affects both the choice of insurance type during enrollment period as
> well as the treatment cost associated with that beneficiary when
> comparing two cohorts.
> 
> Any suggestions regarding how I should treat X2? Should it be included
> in the second stage, GLS regression, of analysis, if so how to
> overcome the case where right hand side variables are function of each
> other? Are there other issues should I worry about while first running
> pscore and then psmathc2?
> 
> As always, thanks in advance for any help provided.
> 
> Zeynal Karaca
> 
> 
> 
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