通过entropy方法得到的 倾向匹配得分运算结果。STATA。
Data Setup
Treatment variable: treat
Covariate adjustment: age educ black (1st order). age educ (2nd order).
Optimizing...
Iteration 1: Max Difference = 15245.0741
Iteration 2: Max Difference = 5598.25812
Iteration 3: Max Difference = 2054.48639
Iteration 4: Max Difference = 760.142692
Iteration 5: Max Difference = 291.381205
Iteration 6: Max Difference = 116.077553
Iteration 7: Max Difference = 45.9603976
Iteration 8: Max Difference = 16.2673747
Iteration 9: Max Difference = 3.95948531
Iteration 10: Max Difference = .368522542
Iteration 11: Max Difference = .00377801
maximum difference smaller than the tolerance level; convergence achieved
Treated units: 185 total of weights: 185
Control units: 15992 total of weights: 185
Before: without weighting
| Treat | Control
| mean variance skewness | mean variance skewness
-------------+---------------------------------+---------------------------------
age | 25.82 51.19 1.115 | 33.23 122 .3478
educ | 10.35 4.043 -.7212 | 12.03 8.242 -.4233
black | .8432 .1329 -1.888 | .07354 .06813 3.268
After: _webal as the weighting variable
| Treat | Control
| mean variance skewness | mean variance skewness
-------------+---------------------------------+---------------------------------
age | 25.82 51.19 1.115 | 25.82 51.2 .6865
educ | 10.35 4.043 -.7212 | 10.35 4.043 -.7021
black | .8432 .1329 -1.888 | .8432 .1322 -1.888
Graphing...




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