在Stata中，如何访问混合命令的结果？

Question

在Stata中运行mixed命令的手动示例：

use http://www.stata-press.com/data/r13/pig
mixed weight week || id:

我得到以下结果：

Performing EM optimization: 

Performing gradient-based optimization: 

Iteration 0:   log likelihood = -1014.9268  
Iteration 1:   log likelihood = -1014.9268  

Computing standard errors:

Mixed-effects ML regression                     Number of obs      =       432
Group variable: id                              Number of groups   =        48

                                                Obs per group: min =         9
                                                               avg =       9.0
                                                               max =         9


                                                Wald chi2(1)       =  25337.49
Log likelihood = -1014.9268                     Prob > chi2        =    0.0000

------------------------------------------------------------------------------
      weight |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        week |   6.209896   .0390124   159.18   0.000     6.133433    6.286359
       _cons |   19.35561   .5974059    32.40   0.000     18.18472    20.52651
------------------------------------------------------------------------------

------------------------------------------------------------------------------
  Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
id: Identity                 |
                  var(_cons) |   14.81751   3.124226      9.801716    22.40002
-----------------------------+------------------------------------------------
               var(Residual) |   4.383264   .3163348      3.805112     5.04926
------------------------------------------------------------------------------
LR test vs. linear regression: chibar2(01) =   472.65 Prob >= chibar2 = 0.0000

我的问题是，我能否以编程方式访问“随机效应参数”的估计：var(_cons)和var(Residual)

我试过查看return(list) & ereturn(list)，但那里似乎没有可用的。

Answer 1

我在加州大学洛杉矶分校的网站上找到了一个选项

* var(cons)
_diparm lns1_1_1, f(exp(@)^2) d(2*exp(@)^2)

* var(Residual)
_diparm lnsig_e, f(exp(@)^2) d(2*exp(@)^2)