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st: RE: psmatch2-identifying matched pairs


From   "Ariel Linden, DrPH" <ariel.linden@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: psmatch2-identifying matched pairs
Date   Mon, 5 Apr 2010 08:40:35 -0700

Hi Garth,

I haven't looked at the specific lines of code in PSMATCH2, but it seems
likely to me that the algorithm runs the ATT, then ATU, then ATE last. Each
iteration will naturally change the matches, since ATT means finding
controls to match to treated, ATU means finding treated to match to
controls, and ATE looks to adjust all units to get at the population average
effect. 

To test this, try running the code in order ATT, ATU, and ATE, and review
the matches after each iteration. See if they change, and if they are
dropped after ATE.

Finally, you can email the authors of PSMATCH2. I have contacted them in the
past and found them very helpful.

Ariel 


Date: Sun, 4 Apr 2010 23:43:32 -0500
From: "Garth Rauscher" <garthr@uic.edu>
Subject: st: RE: RE: psmatch2-identifying matched pairs

Thanks to Ariel for the explanation. To estimate the average treatment
effect in the population (ATE) it makes sense that the 1:1 matching would
not be used. However, with the ATE option in PSMATCH2, the output also
includes estimates of ATT and ATU along with ATE, therefore it would seem
that the program would still need to know the matched pairs in order to
estimate ATT. Therefore I don't understand why the identified pairs change
and some appear to be "broken".

Garth Rauscher
Associate Professor of Epidemiology
Division of Epid/Bios (M/C 923)
UIC School of Public Health
1603 West Taylor Street
Chicago, IL 60612
ph: (312)413-4317
fx:  (312)996-0064
em: garthr@uic.edu
 

- -----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Ariel Linden,
DrPH
Sent: Saturday, April 03, 2010 10:04 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: RE: psmatch2-identifying matched pairs

Garth

Per your question about ATE and dropped matches: That makes intuitive sense
since the ATE represents the average treatment effect in the population.
Therefore, you would need to have the outcome values of the entire
population, not just the subset of matched controls. As a result, you would
no longer have 1:1 matches.

Ariel

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