stata做嵌套logit回归，一直迭代，不出结果

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想通过嵌套logit回归分析【流动人口对流入地的选择】，一共2w6流动人口样本，✖️330个地级市，得到600w+观测数据。数据是平衡的；在查阅了版内其他帖子后，解释变量已经经过了标准化；但只用了四五个解释变量，还是一直迭代，不出结果。
. nlogit choice dis_km time_hour ||type:sex-numfmember||imoption:, noconstant case(id) notree

Iteration 0:   log likelihood = -98601.553  
Iteration 1:   log likelihood = -85214.103  (backed up)
Iteration 2:   log likelihood = -82298.507  (backed up)
Iteration 3:   log likelihood = -81407.222  (backed up)
Iteration 4:   log likelihood = -81322.019  (backed up)
Iteration 5:   log likelihood = -81270.416  (backed up)
Iteration 6:   log likelihood = -81263.177  (backed up)
Iteration 7:   log likelihood = -81254.996  (backed up)
Iteration 8:   log likelihood = -81171.051  (backed up)
Iteration 9:   log likelihood = -81151.431  (backed up)
Iteration 10:  log likelihood = -81147.414  (backed up)
Iteration 11:  log likelihood = -81145.062  (backed up)
Iteration 12:  log likelihood = -81112.848  (backed up)
Iteration 13:  log likelihood = -81073.461  (backed up)
Iteration 14:  log likelihood = -80683.055  (backed up)
Iteration 15:  log likelihood = -79761.494  (backed up)
Iteration 16:  log likelihood = -79761.254  (backed up)
Iteration 17:  log likelihood = -79678.531  (backed up)
Iteration 18:  log likelihood = -79648.733  (backed up)
Iteration 19:  log likelihood = -79641.351  (backed up)
Iteration 20:  log likelihood = -79640.319  (backed up)
Iteration 21:  log likelihood = -78925.954  
Iteration 22:  log likelihood = -78870.406  (backed up)
Iteration 23:  log likelihood = -78831.776  (backed up)
Iteration 24:  log likelihood = -78793.387  (backed up)
Iteration 25:  log likelihood = -78758.775  
Iteration 26:  log likelihood =  -78325.86  
Iteration 27:  log likelihood = -78143.405  
Iteration 28:  log likelihood = -77926.899  
Iteration 29:  log likelihood = -77673.647  
Iteration 30:  log likelihood = -77649.901  
Iteration 31:  log likelihood = -77567.502  
Iteration 32:  log likelihood = -77544.481  
Iteration 33:  log likelihood = -77538.164  
Iteration 34:  log likelihood = -77535.183  
Iteration 35:  log likelihood = -77528.728  
Iteration 36:  log likelihood =   -77518.5  
Iteration 37:  log likelihood = -77517.267  
Iteration 38:  log likelihood = -77516.047  
Iteration 39:  log likelihood = -77515.958  
Iteration 40:  log likelihood = -77515.904  
Iteration 41:  log likelihood = -77515.903  
Iteration 42:  log likelihood = -77515.898  
Iteration 43:  log likelihood = -77515.898  


到iteration43后……模型就再也没了动静QAQ

请各位大佬、老师麻烦帮帮看看，是不是不适合用嵌套Logit回归？

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关键词：嵌套logit Stata logit tata Log

请问解决了吗？

您这个sex-numfmember对不同的type类型来说是不同的值吗？

请问您解决了吗

您好，请问使用嵌套模型中出现报错cannot compute an improvement -- flat region encountered，是出了什么问题呢？

您好，请问解决了吗，最近在写论文遇到了类似的问题

你好问题解决了吗？遇到了同样的问题。