Re: st: RE: MCNEMAR test or Average treatment effects in matched data.

[mccali mccalister <mccali85@hotmail.com>]

Thank you very much.
i will read carrefully the refference you gave me.

Best regrads

Enviado desde mi iPad

> El 07/01/2014, a las 18:29, "Joe Canner" <jcanner1@jhmi.edu> escribió:
> 
> Dr. Ayaon,
> 
> I am not an expert on propensity score matching; I have used it occasionally and was sharing a few insights and experiences since no one else had replied.  I would recommend that you familiarize yourself with the recent literature on the subject.  A good start would be:  Stuart, E.A. (2010). Matching Methods for Causal Inference: A review and a look forward. Statistical Science 25(1): 1-21.
> 
> In a recent thread on this subject, someone recommended against checking for balance using methods like t-tests which are dependent on sample size.  This is certainly a useful caution, depending on the size of your study.  If balance is determined by not rejecting the null hypothesis of no difference, you need to be careful that this result is due to the lack of difference between the groups rather than to insufficient sample size.  If sample size is an issue for you in this regard, then perhaps you can try a non-parametric test.
> 
> Regards,
> Joe
> ________________________________________
> From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of mccali mccalister [mccali85@hotmail.com]
> Sent: Tuesday, January 07, 2014 8:17 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: MCNEMAR test or Average treatment effects in matched data.
> 
> Dear Dr.Canner,
> 
> I really apreciate your replay. So if I understood well, you simply would use the log.regression to see the effect of the my treatment. What about the average treatment effects? Are they usefull? In my case?(the incidence of mediastinitis is the outcome ) Maybe the interpretaion in medical issues is not so clear?So should I avoid it?
> 
> It is very frequent that many paper using propensity score (not necessary should  be right)  they show the new propensity score groups that they are balanaced using parametric tests or non parametric test(even then they use standarizes mean differences). What would you advice me to use if I want to compare baseline caracteristic of my population  before and after the propensity score ? Note that I want to show all the baseline variables and many of them are not included in the propensity score model. Should. I simply use parametric tests weighted by psmatch2?
> 
> Best regards
> Dr. Ayaon
> Cardiovascular resident
> 
> Enviado desde mi iPad
> 
>> El 06/01/2014, a las 23:12, "Joe Canner" <jcanner1@jhmi.edu> escribió:
>> 
>> Dear Dr. Ayaon,
>> 
>> According to a previous thread on this subject (http://www.stata.com/statalist/archive/2012-08/msg00985.html) it is not necessary to used a matched analysis in a 1:k propensity score matched analysis.  In fact, I'm not even sure how one would do a McNemar test for 1:5 matching (although with a little work it might be possible for a 1:1 match).  More to the point, as mentioned in the previous thread, I would question whether propensity score matching truly qualifies as a matched analysis for McNemar purposes.  Two people can have the same (or similar) propensity score even if they have a quite different set of characteristics.
>> 
>> As noted in the previous thread, it should be sufficient (if not preferable) to do a logistic regression of your outcome variable versus the treatment group, weighted using the _weight variable provided by -psmatch2-, and including all of the matching variables (and any other relevant variables) as covariates.
>> 
>> Regards,
>> Joe Canner
>> Johns Hopkins University School of Medicine
>> 
>> ________________________________________
>> From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of mccali mccalister [mccali85@hotmail.com]
>> Sent: Monday, January 06, 2014 4:21 PM
>> To: statalist@hsphsun2.harvard.edu
>> Subject: st: MCNEMAR test or Average treatment effects in matched data.
>> 
>>> 
>>> Hi,
>>> I need some help with matched paired data.
>>> I am working with pared data using PSMATCH2 and TEFFECTS. I do get well balanced data checked with PSTEST. But I do have a question comparing the effect of the treatment ( the reduction of mediastinitis in cardiac surgery ). What should I use? a McNemar test weighted by PSmatch2 ( I did NN-K, 5:1), or should I use simply the ATE, ATET or ATU that I get in the Teffects or Psmatch2.
>>> 
>>> Maybe both are 2 things conceptualy different?
>>> All my data are binomial
>>> Best regards
>>> 
>>> Dr. Ayaon
>>> Cardiovascular resident
>> 
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