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re: st: propensity score matching in 2 stages(if match is not found inside region then match outside)


From   "Ariel Linden, DrPH" <ariel.linden@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   re: st: propensity score matching in 2 stages(if match is not found inside region then match outside)
Date   Wed, 28 Nov 2012 12:08:31 -0500

Hi Auditya,

First off, you mention both the 0.25 caliper and common support in the same
breath. These are mutually exclusive issues and effect the analysis
separately. More specifically (as related to your question):

Calipers: setting the caliper at 0.25 is a rule of thumb, but by no means is
it written in stone. You should try various caliper settings (including NO
caliper at all and setting the algorithm to nearest-neighbor), and see if
that increases sample size while preserving covariate balance. Similarly,
you could forego the matching and use propensity score weighting instead.
That would ensure you use the full set of non-treated (those not-impacted
but the natural disaster).

Common support: this is a more straight-forward issue. Generally speaking,
you should always run your analyses using only those units within common
support. This is to ensure that we are not extrapolating beyond the data.
That said, you should always check the covariate balance with and without
common support, since it is quite possible that if the propensity score is
incorrectly estimated, you could have good covariate balance for units
beyond common support (or vice-versa).

I would start with these items before moving on to a different control group
scenario. I am also not enamored with the mix-and-match approach you
describe, using controls from one area and then supplementing them with
controls from another area. You are running the risk of increasing
unobserved bias. If you want to include different sets of controls, I would
suggest running the matching strategy twice, once using the "local"
controls, and once using the "distant" controls. If the results are similar,
you may have more confidence in your treatment effect estimates.

I hope this helps

Ariel  



Date: Tue, 27 Nov 2012 19:15:50 -0600
From: Auditya Shamsuddin <auditya46@gmail.com>
Subject: st: propensity score matching in 2 stages(if match is not found
inside region then match outside)

Fellow Stata-users
I am a relatively new STATA user.
I am using psmatch2(version 4.0.4 10nov2010 E. Leuven, B. Sianesi) to
find out impact of natural disaster on child labor. Based on the
propensity to be affected by natural disaster, I would like to match
children within same district(same as county in US) i.e., a natural
disaster affected child will be matched with another child from the
same district who has similar likelihood of being affected by the
natural disaster but who is not. To ensure good quality match within
the district, I specify the caliper to be of 0.25 standard deviation
of propensity score. But problem with this condition is that 35 out of
my 105 treatment observations stay out of common support and, this
cannot be used for estimating average treatment effect on the treated.
So, I would like to match these 35 observations, which did not find
close  match within district, with control observations from outside
the district, if close matches exist within 0.25 standard deviation of
propensity score. If a treatment fails to find a match within the
specified caliper even outside the region/district, I will discard
that from the analysis. In brief
i) First stage: matching has to be done within district.
ii) In Second stage the unmatched treatments remaining from the first
stage  will be tried to match with control observations from outside
the region/district.
How can I  use psmatch2 for this? Or, any other package in Stata? I
really lack knowledge on writing program in STATA. Can anyone save me
with this, specifically, how to write code to execute my model. I
appreciate your thought and instruction in advance.
SIncerely
Auditya


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