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From | Alistair Windsor <alistair.windsor@gmail.com> |
To | statalist@hsphsun2.harvard.edu |
Subject | re: re:st: pscore question |
Date | Thu, 10 Feb 2011 16:05:04 -0600 |
Associated to psmatch2 is pstest which looks at covariate imbalance after matching. I also like to run logit/probit regressions on the treatment over the combined treated and pseudo control groups and look for joint vanishing of the non-constant terms using a Wald or likelihood ratio test.
One further option is to look into optmatch for R. This performs optimal matching using a variety of schemes.
The best bet is to try several techniques and see which work best for your purposes.
Yours, Alistair On 2/10/11 1:33 AM, statalist-digest wrote:
Date: Wed, 9 Feb 2011 10:23:19 -0500 From: "Ariel Linden. DrPH"<ariel.linden@gmail.com> Subject: re:st: pscore question Daniel, If you already have a propensity score estimated, you can use psmatch2" (a user written program by Edwin Leuven and Barbara Sianesi). This program allows you to use an existing propscore and it will conduct the necessary tests of balance on covariates. You also asked about blocking - there is another program that naturally "blocks", but is flexible enough to allow you to generate your own blocks. This program is called "cem" [Coarsened Exact Matching], a user-written program by Matthew Blackwell and Gary King at Harvard. Given what you are trying to do, I would probably prefer to use propensity score-based weighting over matching. Austin Nichols wrote a nice paper on that " Erratum and discussion of propensity-score reweighting" in Stata Journal 8(4):532--539 I hope this helps, and good luck! Ariel
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