请教各位大佬,在做面板数据的多项Logit模型的IIA检验,但无法通过,通过查阅相关资料发现,可以用suest,但是做到test那里总说找不到M1,实在不知道怎么回事,求各位大佬解答。代码和模型如下:
quietly mlogit Turnover2ijt Levelij Typeij Authorityij Reciprocityij Provinceij Experiencei Nativeij Assistanceij Policy Agei Agej Tenurei
> Tenurej
.
. estimates store m1,title(all categories)
.
. quietly mlogit Turnover2ijt Levelij Typeij Authorityij Reciprocityij Provinceij Experiencei Nativeij Assistanceij Policy Agei Agej Tenure
> i Tenurej if Turnover2ijt !=1
.
. estimates store m2, title(Turnover2ijt != "平调":Turnover2ijt)
.
. quietly mlogit Turnover2ijt Levelij Typeij Authorityij Reciprocityij Provinceij Experiencei Nativeij Assistanceij Policy Agei Agej Tenure
> i Tenurej if Turnover2ijt !=2
.
. estimates store m3, title(Turnover2ijt != "晋升":Turnover2ijt)
.
. suest m*, noomitted
Simultaneous results for m1, m2, m3
Number of obs = 180,372
-------------------------------------------------------------------------------
| Robust
| Coef. Std. Err. z P>|z| [95% Conf. Interval]
--------------+----------------------------------------------------------------
m1__0_无流动_ |
--------------+----------------------------------------------------------------
m1__1_平调_ |
Levelij | .5618367 .4501543 1.25 0.212 -.3204496 1.444123
Typeij | .9188808 .4341076 2.12 0.034 .0680455 1.769716
Authorityij | 2.324895 .5364115 4.33 0.000 1.273548 3.376242
Reciprocityij | -1.226852 1.257955 -0.98 0.329 -3.692399 1.238695
Provinceij | 1.008672 .4957285 2.03 0.042 .0370622 1.980282
Experiencei | 3.205499 .5630571 5.69 0.000 2.101928 4.309071
Nativeij | -13.86703 .2846984 -48.71 0.000 -14.42503 -13.30903
Assistanceij | 4.484323 1.303015 3.44 0.001 1.930461 7.038186
Policy | .6960337 .6797324 1.02 0.306 -.6362174 2.028285
Agei | -.0336092 .0588053 -0.57 0.568 -.1488655 .0816471
Agej | .0671435 .0466817 1.44 0.150 -.0243509 .158638
Tenurei | -.1108716 .0766407 -1.45 0.148 -.2610845 .0393414
Tenurej | -.0108028 .0772206 -0.14 0.889 -.1621524 .1405468
_cons | -13.14304 3.816531 -3.44 0.001 -20.6233 -5.662775
--------------+----------------------------------------------------------------
m1__2_晋升_ |
Levelij | -.3604523 .2974835 -1.21 0.226 -.9435091 .2226046
Typeij | .4134009 .3607329 1.15 0.252 -.2936225 1.120424
Authorityij | 1.263756 .3114627 4.06 0.000 .6533001 1.874212
Reciprocityij | -.3232281 .9674722 -0.33 0.738 -2.219439 1.572983
Provinceij | .6968765 .3991123 1.75 0.081 -.0853692 1.479122
Experiencei | 2.646878 .5150955 5.14 0.000 1.637309 3.656446
Nativeij | -.0888265 .5821894 -0.15 0.879 -1.229897 1.052244
Assistanceij | 2.702264 1.298849 2.08 0.037 .1565667 5.24796
Policy | -.1420197 .3914999 -0.36 0.717 -.9093454 .6253059
Agei | .0362258 .0466971 0.78 0.438 -.0552989 .1277505
Agej | -.0670411 .0478986 -1.40 0.162 -.1609207 .0268384
Tenurei | -.1313733 .0621248 -2.11 0.034 -.2531356 -.009611
Tenurej | -.0976202 .0771055 -1.27 0.205 -.2487442 .0535037
_cons | -6.226196 3.240363 -1.92 0.055 -12.57719 .1247994
--------------+----------------------------------------------------------------
m2__0_无流动_ |
--------------+----------------------------------------------------------------
m2__2_晋升_ |
Levelij | -.3603463 .2975532 -1.21 0.226 -.9435398 .2228472
Typeij | .4127282 .3609329 1.14 0.253 -.2946873 1.120144
Authorityij | 1.263566 .3115511 4.06 0.000 .6529374 1.874195
Reciprocityij | -.3228565 .9690891 -0.33 0.739 -2.222236 1.576523
Provinceij | .6953463 .3994409 1.74 0.082 -.0875434 1.478236
Experiencei | 2.640829 .5161453 5.12 0.000 1.629203 3.652455
Nativeij | -.0858975 .5818218 -0.15 0.883 -1.226247 1.054452
Assistanceij | 2.69264 1.303344 2.07 0.039 .1381326 5.247148
Policy | -.1421538 .3916241 -0.36 0.717 -.9097229 .6254153
Agei | .0361915 .0467164 0.77 0.439 -.055371 .1277539
Agej | -.0671141 .0478818 -1.40 0.161 -.1609607 .0267325
Tenurei | -.1310913 .0621685 -2.11 0.035 -.2529393 -.0092433
Tenurej | -.0975566 .0771787 -1.26 0.206 -.2488241 .0537109
_cons | -6.221047 3.239899 -1.92 0.055 -12.57113 .129038
--------------+----------------------------------------------------------------
m3__0_无流动_ |
--------------+----------------------------------------------------------------
m3__1_平调_ |
Levelij | .5604684 .4501481 1.25 0.213 -.3218057 1.442742
Typeij | .9171163 .4342031 2.11 0.035 .0660939 1.768139
Authorityij | 2.325131 .5363306 4.34 0.000 1.273943 3.37632
Reciprocityij | -1.234674 1.261822 -0.98 0.328 -3.7078 1.238452
Provinceij | 1.008877 .4959804 2.03 0.042 .036773 1.98098
Experiencei | 3.201134 .5636556 5.68 0.000 2.096389 4.305879
Nativeij | -13.85041 .2814877 -49.20 0.000 -14.40211 -13.2987
Assistanceij | 4.474118 1.307499 3.42 0.001 1.911467 7.03677
Policy | .6909592 .6775586 1.02 0.308 -.6370313 2.01895
Agei | -.0340998 .0589399 -0.58 0.563 -.1496199 .0814202
Agej | .0676175 .0467519 1.45 0.148 -.0240146 .1592496
Tenurei | -.1106198 .0766807 -1.44 0.149 -.2609111 .0396715
Tenurej | -.0107036 .0771499 -0.14 0.890 -.1619147 .1405074
_cons | -13.13811 3.813775 -3.44 0.001 -20.61297 -5.663247
-------------------------------------------------------------------------------
. test [m1__1_平调_] = [m3__1_平调_], cons
m1__1_平调_ not found
r(111);
. test [m1__1_平调] = [m3__1_平调], cons
m1__1_平调 not found
r(111);
. test [m1__2_晋升_ ] = [m2__2_晋升_ ], cons
m1__2_晋升_ not found
r(111);
. test [m1__2_晋升_] = [m2__2_晋升_], cons
m1__2_晋升_ not found
r(111);