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. Author manuscript; available in PMC: 2019 Jun 13.
Published in final edited form as: Proc Mach Learn Res. 2019 Apr;89:2445–2453.

Figure 1:

Figure 1:

Estimated CATT vs. True CATT (Conditional Average Treatment Effect on the Treated). DAME and FLAME perfectly estimate the CATTs before dropping important covariates. DAME matches all units without dropping important covariates, but FLAME needs to stop early in order to avoid poor matches. All other methods are sensitive to irrelevant covariates and give poor estimates. The two numbers on each plot are the number of matched units and MSE.