. import excel "/Users/ElvaYe1/Dropbox/Professional Paper 3.18.23 PM/Variables/2000/PS00_050.xls"
> , sheet("PS00_050") firstrow
. psmatch2 Treat Population Employment Per_capita_income_In_1999_Dollar Vehicle_per_Adult, out(Transit) logit ate
Logistic regression Number of obs = 1074
LR chi2(4) = 8.63
Prob > chi2 = 0.0712
Log likelihood = -254.50046 Pseudo R2 = 0.0167
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Treat | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------------------------+----------------------------------------------------------------
Population | -3.29e-06 .000168 -0.02 0.984 -.0003325 .0003259
Employment | -2.992616 1.160026 -2.58 0.010 -5.266226 -.7190059
Per_capita_income_In_1999_Do~r | -.0000193 .0000138 -1.39 0.164 -.0000464 7.85e-06
Vehicle_per_Adult | 3.745785 1.568122 2.39 0.017 .6723213 6.819248
_cons | -1.112405 .7788368 -1.43 0.153 -2.638897 .4140874
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There are observations with identical propensity score values.
The sort order of the data could affect your results.
Make sure that the sort order is random before calling psmatch2.
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Variable Sample | Treated Controls Difference S.E. T-stat
----------------------------+-----------------------------------------------------------
Transit Unmatched | .159840045 .176998178 -.017158133 .035585768 -0.48
ATT | .159840045 .240613309 -.080773263 .063191754 -1.28
ATU | .176998178 .145713652 -.031284526 . .
ATE | -.034510049 . .
----------------------------+-----------------------------------------------------------
Note: S.E. does not take into account that the propensity score is estimated.
| psmatch2:
psmatch2: | Common
Treatment | support
assignment | On suppor | Total
-----------+-----------+----------
Untreated | 1,004 | 1,004
Treated | 70 | 70
-----------+-----------+----------
Total | 1,074 | 1,074 回归分析不是y=(x1+x2+x3+x4+......+xn)+β(dummy variable)么?想知道β是哪个数?Log likelihood, _cons,ATT, ATU,ATE都是干嘛用的……
LR chi2(4)=8.63,Prob > chi2 = 0.0712,Log likelihood = -254.50046 Pseudo R2 = 0.0167都是啥意思?
[em06][em06]
请不要嘲笑我[em06]