Hi everyone,

I am using propensity score matching for my research. I wanted to use esttab to create a table of ATT after using psmatch2


Code:
global HH rel educ married age
global MTH jan feb mar apr
then i use nearest neighbor matching
Code:
psmatch2 treat $HH, neighbor(5) outcome($MTH)
after this I cannot figure out how I can use the information to have professional looking tables. I tried to use

Code:
esttab , cells(b se t)


but this only gave the unmatched value and not the ATT. I want to show at what level of significance is the results. Should i just regress each outcome individually


Code:
psmatch2 treat $HH, neighbor(5) outcome($MTH)
foreach outcome in $MTH {
    reg `outcome' treat $HH [pw = _weight], robust


and make the tables manually but I have a lot of outcome variables as well as variables I am using to balance my treatment and control groups (I couldn't put it all here as there is a limit on how much data we can post).

I would appreciate any help suggestions or guidance to the right direction.

Thank you!


* Example generated by -dataex-. To install: ssc install dataex
clear
input byte(rel educ) float(married age) byte(jan feb mar apr treat)
1 3 1 44 0 0 0 0 3
1 3 1 67 0 0 1 1 0
1 3 0 60 0 0 0 1 1
1 3 0 61 0 0 0 0 0
1 4 0 73 0 0 0 0 0
1 3 0 55 1 1 0 0 0
1 1 0 76 0 0 1 1 0
1 3 1 47 0 0 0 0 1
1 1 0 82 1 1 1 0 0
1 3 0 61 0 0 1 1 1
1 5 1 32 0 0 0 0 1
1 3 1 52 0 0 1 1 0
1 7 1 44 1 1 0 0 0
1 3 1 42 0 0 0 1 2
1 3 1 42 0 0 1 0 1
1 3 0 59 0 0 0 0 2
1 3 0 38 1 1 0 0 0
1 3 1 59 0 0 0 0 1
1 3 1 50 0 0 1 0 1
1 4 0 50 1 1 0 0 1
1 1 0 82 1 0 1 1 1
1 3 1 36 0 0 0 0 0
1 3 0 50 0 0 0 0 0
1 4 0 66 1 1 1 0 0
1 3 0 52 1 1 1 1 0
1 3 0 48 0 1 0 0 1
1 4 0 61 0 0 1 1 0
1 3 0 43 1 1 0 0 0
1 4 1 64 1 0 0 0 0
1 3 0 56 0 0 1 0 0
1 4 0 40 0 1 0 0 0
1 2 1 51 0 0 1 1 1
1 3 1 53 0 0 0 0 1
1 3 0 63 0 0 0 0 2
1 1 0 63 0 0 0 1 1
1 6 0 55 1 1 1 0 0
1 4 0 63 0 0 0 0 0
1 4 0 69 0 0 0 0 0
1 3 1 43 0 0 0 1 1
1 10 0 80 0 0 0 0 1
1 3 1 57 0 0 0 0 0
1 3 0 56 0 1 0 0 0
1 3 0 47 0 0 1 1 0
1 1 0 60 0 0 0 0 0
1 3 0 51 1 0 0 0 1
1 1 0 71 0 0 0 0 0
1 4 1 38 1 1 1 0 0
1 3 0 61 0 0 1 1 0
1 3 1 54 0 0 0 0 1
1 4 0 56 0 0 0 1 1
1 3 0 43 0 1 1 0 0
1 1 0 77 0 0 1 1 0
1 4 0 68 0 0 0 0 0
1 3 0 55 1 1 0 0 2
1 10 1 84 0 1 1 0 0
1 4 1 38 0 0 0 0 0
1 3 0 50 0 0 1 1 0
1 4 0 46 0 1 1 0 1
1 3 0 56 1 1 0 0 0
1 5 0 43 0 0 0 0 0
1 5 1 39 0 1 1 0 0
1 1 0 57 0 0 1 1 2
1 3 1 56 0 0 0 0 0
1 3 0 49 0 0 1 1 1
1 1 0 71 1 1 0 0 0
1 1 0 68 0 0 1 0 0
1 3 0 52 0 0 1 1 0
1 3 0 62 1 1 1 1 0
1 3 0 32 0 0 0 1 0
1 6 0 69 0 0 0 0 0
1 3 1 59 0 1 1 1 1
1 3 0 64 0 0 1 0 2
1 1 0 84 0 1 1 1 0
1 3 0 63 0 0 0 0 0
1 4 0 61 0 0 0 0 0
1 4 0 76 1 1 1 0 0
1 3 0 58 0 1 1 0 1
1 3 0 35 0 0 1 1 0
1 3 0 52 0 0 1 1 0
1 6 0 47 1 1 1 0 0
1 3 0 61 0 0 1 0 2
1 2 0 60 0 0 1 0 0
1 1 0 71 0 0 0 0 0
1 4 0 66 0 0 0 0 0
1 1 0 69 0 0 0 0 1
1 1 0 58 1 1 1 0 1
1 3 0 69 0 0 0 0 0
1 4 0 58 0 0 0 1 3
1 3 0 57 0 0 1 1 0
1 4 0 66 1 1 0 0 0
1 1 0 81 0 0 0 0 2
1 3 0 49 0 1 1 1 0
1 5 0 36 1 1 1 0 0
1 4 0 49 1 1 1 0 0
1 4 0 56 1 1 1 0 0
1 5 0 75 1 1 0 0 1
1 4 1 45 1 1 1 0 0
1 7 1 74 1 0 0 0 1
1 3 0 49 0 0 0 0 2
1 3 0 52 1 1 1 1 1
end
[/CODE]