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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.