In an administrative database research using retrospective cohort study design, the propensity score matching may be adopted to ensure group A and group B in the cohort will look similar (balanced) in a bunch of relevant covariates. What is the best statistical software to use for applying a matching algorithm?
Given most software (ex: R, SPSS, SAS, MATLAB, STATA) provide solutions to do what you want to do, I would choose the one you also will find most useful in the future. I have been using SPSS, STATA and MATLAB and find STATA to be the most adapted for biomedical statistical analysis.
You can then download and use the -ccmatch- command generated by Daniel Cook.
http://ideas.repec.org/c/boc/bocode/s457372.html
This can be done by simply typing "find it ccmatch" in the command box.
To understand how to enter variables type "help ccmatch" in the command box.
Do not forget that the analysis must then account for the matched structure and you cannot use simple methods to measure relative risks.
In STATA, the command for measuring relative risk for a matched cohort is -csmatch-
http://www.stata-journal.com/sjpdf.html?articlenum=st0070
When using logistic regression, you need to use conditional logistic regression using the following command:
xi: clogit “case” i.”exposure”, strata(“pairs/set”) or
Stata is better
Please find the attched guideline how to use it
Stata is better
the attached presentations guide you how to use propensity score matching in STATA
It depends to a great extent on which software you're comfortable working with. I use SAS, and have found the in-built macros to be quite easy to implement while PS matching. I've attached a link that might be helpful.
Thanks
Why nobody mentioned Matchit package in R language? It is quite straightforward and gives you so many details. And you visualize the result directly!
Stata and R are the best, to my knowledge. The last time I checked, SAS did not include any built-in way to assess the balance of the propensity score or the balance of the covariates within strata of the propensity score.
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