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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: propensity score and mills ratio |

Date |
Tue, 28 Oct 2008 13:23:21 +0100 |

This is a line for the server to eat http://www.stata-journal.com/article.html?article=st0136 HTH Martin -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of francesca.modena Sent: Tuesday, October 28, 2008 12:40 PM To: statalist@hsphsun2.harvard.edu Subject: st: propensity score and mills ratio Dear all, This is a classical problem of treatment effect. I have two outcomes: Y1i: the outcome of unit i if i were exposed to the treatment (T=1) Y0i: the outcome of unit i if i were not exposed to the treatment (T=0) I want to regress Y1i on a set of characteristics Z. OLS regression of Y1i on Z can be biased because of sample selection problem. Let us assume that the probability of being exposed to the treatment can be described by a probit equation Ti = alpha*X + error >From the probit equation I can derive the selection terms for the two groups T=0 and T=1 (i.e. inverse mills ratio) Now I can consistently regress Y1i on Z for the sample with T=1, augmenting the regression with the corresponding selection term (i.e. I include the mills ratio for those with T=1 in the regression). Another procedure to deal with selection bias is the propensity score matching. If I am right the Stata commands are: pscore treat X, pscore(scorename) attr Y1i treat, pscore(scorename) (Is this equation estimated on all the sample or only for those with T=1 or T=0?) What is the difference between the two procedures? Can I use both mills ratio and propensity score to deal with selection problems? Thanks Francesca * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: propensity score and mills ratio***From:*"francesca.modena" <francesca.modena@email.unitn.it>

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