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st: Re: Propensity Score Matching

From   niken kusumawardhani <>
Subject   st: Re: Propensity Score Matching
Date   Fri, 22 Jun 2012 13:53:57 -0700 (PDT)

Dear Ariel, thank you for your information, that's a great help! 

My goal is to prove that using weighted regression with the weights provided
by psmatch2 will yield the same result as directly typing psmatch2 x,
pscore(_ps) outcome(y). So you really answered my question, thanks again!

I have another question. Hope that anyone in this forum could explain to
me.. I understand that the variable _weight in psmatch2 gives you
information on the value of weight generated by psmatch2. To be more
precise, let me describe my dataset. it consists of 702 treated observations
and 289 control. For example: I try with nearest neighbor matching without
replacement, and obtain 280 treated and 280 control under common support.
The variable _weight has 560 values, with all weight equals 1. So basically
all observations under common support has its weight.

But what makes me confused is, when I try matching with replacement, not
every observation has the weight. Under this algorithm, I get 630 treated
and 289 control under common support. However, the variable _weight only
contains 650 values: 623 for treated, and 27 for control. Moreover, for
control observations, the value of weight is so big, like 30 and 60. I don't
understand how it works.. If by using 'without replacement' I have 289
control, doesn't it mean under 'with replacement' I should have at least
similar number of control observations? And why does for NN matching with
replacement, some observations under common support have missing data for
the weight?

Thanks before!



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