I am trying to understand some of the heterogeneity in my study in which I am working by matching data. I am estimating the effect of treatment on Y matching on two controls. To estimate the effect I am using the following teffects command:
Code:
teffects psmatch (Y) (treatment dist_control dir_control, logit), control(0) //can't use rdist - perfectly predicts in some cases
Your help would be highly appreciated.
Thanks,
John
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float Y long treatment float dir_control double dist_control 11501085 1 9 7 18502764 1 0 21 45422704 0 3 797 57362584 1 1 518 3086949 1 0 203 33602376 1 18 704 63366988 0 0 319 12594366 0 0 82 103255616 0 4 704 34128948 0 1 673 49481792 0 2 508 6682098 1 9 179 255873248 0 0 439 10327239 1 12 128 50632036 0 4 369 144097792 0 3 179 14438661 0 0 497 154696080 0 2 641 15464507 0 0 162 6838070 1 0 15 44862188 1 1 228 80270224 0 2 797 39363636 1 1 17 37861964 0 5 102 388532 0 0 155 21386012 1 11 476 28154936 0 2 334 100138848 0 1 317 48463480 0 6 644 15977832 1 9 153 11841544 1 0 276 30547218 1 1 134 270700 0 0 509 8363518 0 2 431 66027236 0 0 651 6971777 1 1 518 66641204 0 7 565 23864886 0 1 213 31558040 1 0 31 11540607 1 0 17 5095038 1 1 287 3793614 1 0 28 19889300 0 6 369 1844610 1 1 588 6283742 1 0 23 8064972 1 1 213 18655776 0 5 545 99880736 1 4 446 13637433 1 5 190 6995302 1 5 486 end
0 Response to Graph treatment effects by propensity score
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