Fitting constant-only model:  
  
Iteration 0:   log likelihood = -443.83224   
Iteration 1:   log likelihood = -434.46106   
Iteration 2:   log likelihood = -434.28071   
Iteration 3:   log likelihood = -434.28062   
Iteration 4:   log likelihood = -434.28062   
  
Fitting full model:  
  
Iteration 0:   log likelihood = -376.16864   
Iteration 1:   log likelihood = -366.50632   
Iteration 2:   log likelihood = -366.46842   
Iteration 3:   log likelihood = -366.46841   
  
Interval regression Number of obs   = 210
 LR chi2(18)     = 135.62
Log likelihood = -366.46841 Prob > chi2     = 0
  
  
Coef.   Std. Err.      z P>z     [95% Conf. Interval]
  
area    2.932133   1.528826     1.92 0.055    -.0643104 5.928576
housep   -448.7348   521.3713    -0.86 0.389    -1470.604 573.1342
housel   -386.1795   485.2712    -0.80 0.426    -1337.294 564.9345
houseg    351.7442   509.3611     0.69 0.490    -646.5852 1350.074
ring2    1120.952   180.2664     6.22 0.000     767.6361 1474.267
ring23    855.7064   190.1817     4.50 0.000      482.957 1228.456
ring34    728.4232   175.6007     4.15 0.000     384.2522 1072.594
ring45    583.4251   170.3976     3.42 0.001     249.4519 917.3983
ring56    293.4095   165.9506     1.77 0.077    -31.84764 618.6666
housej    83.86826   213.5533     0.39 0.695    -334.6884 502.4249
housef   -31.00832   183.5519    -0.17 0.866    -390.7634 328.7468
houses    87.40535   134.8948     0.65 0.517    -176.9837 351.7944
houseo    4.321604   340.6107     0.01 0.990    -663.2631 671.9063
housegy   -949.5011   126.2009    -7.52 0.000     -1196.85 -702.152
safety    62.90476     62.887     1.00 0.317     -60.3515 186.161
facility    49.41404   54.26319     0.91 0.362    -56.93985 155.7679
service    35.29336   46.35913     0.76 0.446    -55.56886 126.1556
manage   -.6540509   45.96462    -0.01 0.989    -90.74304 89.43494
_cons    786.0277   547.1169     1.44 0.151    -286.3017 1858.357
  
/lnsigma    6.458834    .060526   106.71 0.000     6.340206 6.577463
  
sigma    638.3166   38.63477 566.9128 718.7138
  
  
Observation summary:         0     uncensored observations 
33  left-censored observations 
19 right-censored observations 
158       interval observations 
  

每个自变量对应的z值怎么判断大小？一般都是用t值的，为什么这里是z值呢？二者能转化么？

还有下面的sigma有什么用？ 

请高手指教！！！

多谢！！！