蓝色 发表于 2020-3-25 07:28 
没有问题啊,stata13也是可以出来的
不知道你stata怎么安装的
下载一个安装版的stata,然后默认安装 ...
sysuse auto,clear
(1978 Automobile Data)
. reg price weight length if foreign==0
Source | SS df MS Number of obs = 52
-------------+------------------------------ F( 2, 49) = 29.28
Model | 266348916 2 133174458 Prob > F = 0.0000
Residual | 222845885 49 4547875.2 R-squared = 0.5445
-------------+------------------------------ Adj R-squared = 0.5259
Total | 489194801 51 9592054.92 Root MSE = 2132.6
------------------------------------------------------------------------------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
weight | 6.19526 1.10254 5.62 0.000 3.979623 8.410897
length | -120.5376 38.24525 -3.15 0.003 -197.3943 -43.68088
_cons | 9163.626 4381.408 2.09 0.042 358.8579 17968.4
------------------------------------------------------------------------------
. est store m0
. reg price weight length if foreign==1
Source | SS df MS Number of obs = 22
-------------+------------------------------ F( 2, 19) = 34.72
Model | 113350528 2 56675264 Prob > F = 0.0000
Residual | 31012684.7 19 1632246.56 R-squared = 0.7852
-------------+------------------------------ Adj R-squared = 0.7626
Total | 144363213 21 6874438.7 Root MSE = 1277.6
------------------------------------------------------------------------------
price | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
weight | 4.937235 1.557596 3.17 0.005 1.677149 8.197321
length | 14.76399 49.29231 0.30 0.768 -88.406 117.934
_cons | -7537.909 5247.076 -1.44 0.167 -18520.17 3444.348
------------------------------------------------------------------------------
. est store m1
. suest m0 m1
Simultaneous results for m0, m1
Number of obs = 74
------------------------------------------------------------------------------
| Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
m0_mean |
weight | 6.19526 1.803799 3.43 0.001 2.659879 9.73064
length | -120.5376 60.26334 -2.00 0.045 -238.6516 -2.42361
_cons | 9163.626 6331.454 1.45 0.148 -3245.796 21573.05
-------------+----------------------------------------------------------------
m0_lnvar |
_cons | 15.33017 .2125803 72.11 0.000 14.91352 15.74682
-------------+----------------------------------------------------------------
m1_mean |
weight | 4.937235 1.276321 3.87 0.000 2.435691 7.438779
length | 14.76399 36.54753 0.40 0.686 -56.86785 86.39583
_cons | -7537.909 3677.29 -2.05 0.040 -14745.26 -330.5537
-------------+----------------------------------------------------------------
m1_lnvar |
_cons | 14.30547 .2200134 65.02 0.000 13.87425 14.73669
------------------------------------------------------------------------------
. test [m0_mean] weight = [m1_mean] weight
m0_mean not found
r(111);
.