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re: st: Pstest bias reduction

From   "Ariel Linden, DrPH" <[email protected]>
To   <[email protected]>
Subject   re: st: Pstest bias reduction
Date   Mon, 26 Mar 2012 10:35:05 -0400

Nick, now that you have been properly chastised for following the rules of
the statalist, let me respond to your question. -pstest- (a user written
program by Edwin Leuven & Barbara Sianesi and found on ssc) uses the logic
set forth in the paper by Rosenbaum and Rubin (1985) listed below by Daniel.

Specifically, the standardized residual is first calculated on the total
unadjusted sample using the formula: difference in means/pooled standard

Next, the standardized residual is then calculated on the reduced subset
(matched set of treatment vs controls) using the new difference in means as
the numerator and the original (total sample) pooled standard deviation in
the denominator. Thus, holding the variability constant, the difference in
the first and second calculations represents the " bias reduction." 

I hope this helps


Date: Sun, 25 Mar 2012 19:04:13 -0400
From: Nick Sauers <[email protected]>
Subject: st: Pstest bias reduction

I used Stata for propensity score matching. Â After completing my match, I
ran the Pstest command, and I'm unable to interpret the column that
reports bias. How is bias calculated in Pstest? I've tried multiple
calculations, and my numbers don't align with the  output.


Nick Sauers
[email protected]

Date: Mon, 26 Mar 2012 02:50:00 +0200
From: daniel klein <[email protected]>
Subject: st: Pstest bias reduction


as recently stated
( there
is a convention on Statalist to use - - to indicate Stata code or
commands, which in your case means write -pstest- not Pstest.

More important, you are also asked to explain where user-written
software comes from
( -pstest-
comes with the -psmatch2- package from SSC.

The FAQ also asks you to read the online help before posting a
question (
In your case the help file for -pstest- states

"(b) [...]  The standardised bias is the difference of the sample
means in the treated and non-treated (full or matched) sub-samples as
a percentage of the square root of the average of the sample variances
in the treated and non-treated groups (formulae from Rosenbaum and
Rubin, 1985)."

along with the full reference

Rosenbaum, P.R. and Rubin, D.B. (1985), "Constructing a Control Group
Using Multivariate Matched Sampling Methods that Incorporate the
Propensity Score", The American Statistician 39(1), 33-38.

The article is found here:

If the article does not provide an answer to your question, consider a
more detailed explanation of what exactly you did when trying
"multiple calculations".


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