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| From | "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu> |
| To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
| Subject | RE: st: Re: psmatch2 question |
| Date | Wed, 25 Aug 2010 13:35:10 -0700 |
Since there has been a great deal of interest in matching lately, there is a neat article in Statistical Science, v. 25 #1 by Elizabeth A Stuart entitled Matching Methods for Causal Inference: A Review and a Look Forward. The IMS makes everything available on line so you can get it from http://www.imstat.org/publications/eaccess.htm Tony ________________________________________ From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of anna bargagliotti [abargag@yahoo.com] Sent: Tuesday, August 24, 2010 4:23 PM To: statalist@hsphsun2.harvard.edu Subject: Re: st: Re: psmatch2 question Thank you for your insights about bootstrapping. I wiill try adjusting your code to my situation to reproduce the T-stat and compute the p-value. I am, however, still confused about two very simple things: 1. What is the T-stat for the ATT actually telling us? Is this the T-stat for the comparison of treatment vs control matched groups? 2. How do we determine if there is a treatment effect? * * 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/