In this short article, I explain the Mahalanobis metric matching method and how it can be easily implemented in R. The article is published at Towards Data Science.
Preview: My previous post shows how the propensity score matching can be implemented using 13 lines of R codes. Though those codes, you can see that matching is much about data pre-processing. The idea is to find control units that are comparable to the treated units, so we can attribute the differences in the outcome between treatment groups to the treatment with more confidence. Besides, I want to argue that matching is, in fact, simple, so you should not be terrified by it.
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