Re: st: Propensity score matching: Must all treated samples have a counterfactual?

["Ariel Linden, DrPH" <ariel.linden@gmail.com>]

I feel like a broken record, however I will suggest (as I do to most posters
about propensity score matching) that you read some basic literature on
propensity score matching. In particular Stuart (2010) and Caliendo &
Kopeinig (2008).

First off, when using a matching strategy, if a treated individual does not
have a matched control, it means that there is no counterfactual for that
case. This could be a situation where they are at the extreme end of the
propensity score range, or if your matching algorithm matched too many
controls to a given treated individual, leaving no controls for the next
treated individual.

I suggest you consider using common support, so that you won't have "missing
counterfactuals" at the tails, and I suggest you ask yourself why are you
choosing this particular approach? You certainly have not given us any
insights as to why you have chosen radius matching and nearest neighbor
matching (which are two different algorithms - unless you mean to say
caliper instead of radius?)...

As for your statement   " nearest 3 within +- x score", I assume that you're
referring to the caliper, but it is not clear. The general rule of thumb is
to use a caliper of 0.20 to 0.25 of the standard deviation of the propensity
score (see references below for brief review and further references).
However, you'll have to decide for yourself what is a reasonable caliper
that optimizes balance on covariates. In other words, too large of a caliper
may result in reducing balance, while too narrow of a caliper will limit
matched sample size...

Ariel

References :
Stuart, E.A. (2010) Matching methods for causal inference: a review and a
look forward. Statistical Science, 25(1), 1-21.

Caliendo, M. Kopeinig, S. (2008) Some practical guidance for the
implementation of propensity score matching. Journal of Economic Surveys,
22, 31-72. 

Date: Fri, 16 Aug 2013 14:57:09 +0100
From: Ricky Lim <ricky.lim12345@gmail.com>
Subject: st: Propensity score matching: Must all treated samples have a
counterfactual?

Dear Statalisters,

I ran running propensity score matching using -pscore- and would like
to do radius & nearest neighbour matching (nearest 3 within +- x
score).
15 out of 20 of my treated samples have more than 3 counterfactuals
within 0.05 scores,
whereas the remaining 5 have 1 or none.
Their propensity scores are at the extreme and I would need to
increase the range to +-0.5 before they will have 3 counterfactuals
each.

My questions are:
1. Must every treated sample have a counterfactual / control?
2. Is a radius of 0.5 score too wide? Is it be acceptable to use the
nearest 3 within 0.5 score?

Any advice is deeply appreciated.

Thank you very much in advanced.

Regards,
Ricky

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/