Code:
Code:
teffects psmatch (mexp) (treat mrq mexporter mimp mhcnt mfor divcode*, logit), nneighbor(5) generate(nn5_) gen matched = treat == 1 local sampsize = _N // Nearest Neighbour = 5 Generate when an observation is in the match quietly forvalues i = 1/`sampsize' { if treatTailoredEver[`i'] == 1 { local match1 = nn5_1[`i'] local match2 = nn5_2[`i'] local match3 = nn5_3[`i'] local match4 = nn5_4[`i'] local match5 = nn5_5[`i'] replace matched = 1 in `match1' replace matched = 1 in `match2' replace matched = 1 in `match3' replace matched = 1 in `match4' replace matched = 1 in `match5' } }
Code:
'.' invalid observation number
Yet the underlying issue, which is likely due to my inexperience on teffects, is that I do not know under what situations teffects will fail to find all 5 neighbours on a propensity score matching, but yet itself does not fail due to a failure in the overlap assumption. I would be grateful for any insights anyone has on this.
As an aside, the forvalues loop executes fairly quickly, but if anyone has suggestions on a more elegant solution to the loop, I'm all ears. Thanks!
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