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The application of Propensity Score Matching

Propensity Score Matching is a statistical matching technique that attempts to estimate the effect of a treatment, policy or other intervention by accounting for the covariates that predict receiving the treatment. It helps to reduce bias due to confounding and can be used to estimate the counterfactual outcome.

For example, many of you will have been to a particular university or school and achieved a certain result. But have you ever wondered what could have been the result if you had attended somewhere else (the counterfactual outcome) ? To determine this you would need to account for the covariates using information on people like yourself who studied the same course. Then, you could estimate this counterfactual outcome using Propensity Score Matching.

I have put various resources (including SAS code) on my blog. These have allowed me to do Propensity Score Matching - See blog post here: What could propensity score matching do for you ? (with examples fr....

 

Ian Morton has built propensity scoring models for the financial services sector, for a utility company, and for the public sector. He has given a number of presentations on the technique of propensity score matching, and has also co-authored a forthcoming peer-reviewed journal article.

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Comment by Vincent Granville on May 16, 2013 at 9:33am

Or what if you didn't attend University? For most, this would translate into a lower earnings, maybe lower happiness, more difficult to date smart people etc. But for some, it would be the opposite - providing the opportunity to start a business at 18 years old rather than much later. A good scoring system should be able to predict who can benefit from not earning a degree. 

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