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st: Imbalance in control versus treated group, and weights


From   <Alexander.Severinsen@telenor.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Imbalance in control versus treated group, and weights
Date   Wed, 8 Oct 2008 18:23:19 +0200

Dear Statalisters,

I have the following problem. I have given a sample of 10000 people as targets for receiving an offer, and I have a control group equal to 5000 people. I know that the potentially treated and the controlgroup is representative. However, without my knowledge only 8000 of the 10000 targets were treated, and a specific criteria was used to pick those 8000 from the 10000.

This has created an imbalance between my controlgroup and those treated, and this imbalance is identified and only concerns one variable. I want to investigate whether the offer given could reduce the defection rate of customers, but the variable that created this imbalance is known to hugely impact the defection rate. To reduce this problem I would like to use weights in Stata, but I am unsure on how to approach this? Any tips would be greatly appreciated.

Also, say that I did not correct for this, and did the following probit model with the following variables, y=defected/not defected, x=treated/control, z=factor that created imbalance:
        y=b0+b1*x+b2*z
would it be appropriate to say that it was possible to control for the imbalance by including it as a independent variable in this fashion?

Best wishes,
Alexander Severinsen

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