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re: Re: st: Standardized difference of means after PS matching


From   "Ariel Linden. DrPH" <ariel.linden@gmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   re: Re: st: Standardized difference of means after PS matching
Date   Thu, 30 Aug 2012 10:19:18 -0700

Hi Adam,

I am not sure what is going on with your data. I do suggest that you run
-pstest- after -psmatch2- (both programs found on ssc), and see what results
you get.  

You are correct in using standardized differences for balance checking and
not p-values. -pstest- does provide std. diff. according to Rosenbaum and
Rubin (1985)*, which first calculates the std. diff of the unmatched sample,
and then again using the matched sample. The output provides a "percent bias
reduction", which represents the difference between the unmatched and
matched std.diff. 

This may be the best solution for you rather than trying to figure out why
the estimates differ running it through two different programs.

 Ariel

*Rosenbaum PR, Rubin DB. Constructing a control group using  multivariate
matched sampling methods that incorporate the propensity score. The American
Statistician 1985;39(1):33-38.


Date: Wed, 29 Aug 2012 17:25:50 -0400
From: Adam Olszewski <adam.olszewski@gmail.com>
Subject: Re: st: Standardized difference of means after PS matching

Hi Ariel,
Thanks for the email. I'll try to clarify:

I run something like:
. psmatch2 treat age sex i.race ..., (I use radius matching BTW)
. xi: pbalchk treat age i.sex i.race ...., weight(_weight)

and get output of the kind:
1.race            SDM 0.21
2.race            SDM 0.18   (I'm making the numbers up but this is the
range)

Then I try to run:
.psmatch2 treat age sex race ...,   (which treats "race" as a
continuous rather than factor variable)
.xi: pbalchk treat age i.sex i.race,  weight(_weight)

and get:
1.race           SDM 0.05
2.race           SDM 0.06

The change between "i.race" and "race" in the psmatch2 model is the
only change I made (I think I initially did it by mistake actually),
and was surprised to see the difference.
I tend not to use -pstest- or other tests that use sample-size
dependent p-values, following PC Austin recommendation. Though perhaps
I should take a look if -pstest- would report any change in bias
reduction.

On Wed, Aug 29, 2012 at 5:12 PM, Ariel Linden. DrPH
<ariel.linden@gmail.com> wrote:
> Hi Adam,
>
> It is not clear to me what step in your process is giving you different
> results? In which program are you using c.race vs i.race? I am not sure
that
> -pbalchk- (user written program by Mark Lunt) accepts the prefix -c.- and
> furthermore, I don't understand why you'd treat a multiple categorical
> variable (such as race) as continuous to begin with? You'd certainly end
up
> with a result that would be meaningless.
>
> As far as calculating balance on a binary variable (assuming it is
binary),
> your results should not differ much (between treating the variable as
> continuous and eliciting a proportion, or treating it as a count and using
> chi2) if you have sufficient sample sizes (see what happens when you
compare
> chi2 with t-test for proportions)... However, if you have a multiple
> categorical variable, then I believe you'd need to create dummies for use
in
> -pbalchk-
>
> In any case, I can't really provide more guidance, since I not sure
exactly
> what is going on given the limited information you provided.
>
> Ariel

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