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I wonder if there is a way to identify the MDE (Minimum Detectable Effect) in a propensity score matching (PSM) model for the average treatment effect on the treated (ATT). I am using STATA 14 with the command psmatch2. But I can learn another software. Suppose that

 T= treatment status (1 treated , 0 control)
 X= confounders
 Y = output

First I estimate the propensity score

 logit T x1 x2 .... xn
 predict scoring

Then I use the command psmatch2 to find the ATT.

 psmatch2  T   ,   kernel  out( Y )  pscore(scoring) 

I know that there are some formulas and software to estimate the MDE and the power for randomized experiment and regression discontinuity, but I don´t know a similar formula for matching.

Suppose that I find a ATT effect of 3% that is not statistically significant, in this case I want to know if $ ATT<MDE$.

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