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

**Follow-Ups**:**st: Accidental log***From:*Steve Samuels <sjsamuels@gmail.com>

**Re: st: Standardized difference of means after PS matching***From:*Steve Samuels <sjsamuels@gmail.com>

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