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  • #16
    The remaining variable results are as followed:

    Code:
     Predictive margins                              Number of obs     =      9,458
    Model VCE    : OIM
    
    Expression   : Pr(A170==6), predict(outcome (6))
    
    1._at        : quantX0472      =           0
    
    2._at        : quantX0472      =           1
    
    3._at        : quantX0473      =           0
    
    4._at        : quantX0473      =           1
    
    5._at        : quantX0474      =           0
    
    6._at        : quantX0474      =           1
    
    7._at        : relative2       =           0
    
    8._at        : relative2       =           1
    
    9._at        : relative3       =           0
    
    10._at       : relative3       =           1
    
    11._at       : relative4       =           0
    
    12._at       : relative4       =           1
    
    13._at       : marriage        =           0
    
    14._at       : marriage        =           1
    
    15._at       : IU0             =        .747
    
    16._at       : X011            =         2.6
    
    17._at       : X003            =       39.17
    
    ------------------------------------------------------------------------------
                 |            Delta-method
                 |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
             _at |
              1  |   .0659772    .003817    17.28   0.000      .058496    .0734585
              2  |   .1133882    .006058    18.72   0.000     .1015147    .1252617
              3  |   .0672797   .0029593    22.74   0.000     .0614796    .0730798
              4  |   .1776509   .0123581    14.38   0.000     .1534295    .2018723
              5  |   .0492205   .0035433    13.89   0.000     .0422757    .0561653
              6  |   .1647399    .012964    12.71   0.000     .1393308     .190149
              7  |    .098202   .0037686    26.06   0.000     .0908157    .1055883
              8  |    .050772    .006651     7.63   0.000     .0377363    .0638077
              9  |   .0979507   .0035934    27.26   0.000     .0909078    .1049936
             10  |   .0207947    .008947     2.32   0.020     .0032589    .0383305
             11  |    .115669   .0050211    23.04   0.000     .1058279    .1255101
             12  |  -.0421235   .0107233    -3.93   0.000    -.0631409   -.0211062
             13  |   .0702149   .0076901     9.13   0.000     .0551427    .0852871
             14  |   .0885738   .0030359    29.18   0.000     .0826236    .0945241
             15  |    .087774   .0028923    30.35   0.000     .0821052    .0934428
             16  |   .0871265   .0028713    30.34   0.000     .0814988    .0927543
             17  |   .0870935   .0028949    30.08   0.000     .0814195    .0927674
    ------------------------------------------------------------------------------
    
    Predictive margins                              Number of obs     =      9,458
    Model VCE    : OIM
    
    Expression   : Pr(A170==7), predict(outcome (7))
    
    1._at        : quantX0472      =           0
    
    2._at        : quantX0472      =           1
    
    3._at        : quantX0473      =           0
    
    4._at        : quantX0473      =           1
    
    5._at        : quantX0474      =           0
    
    6._at        : quantX0474      =           1
    
    7._at        : relative2       =           0
    
    8._at        : relative2       =           1
    
    9._at        : relative3       =           0
    
    10._at       : relative3       =           1
    
    11._at       : relative4       =           0
    
    12._at       : relative4       =           1
    
    13._at       : marriage        =           0
    
    14._at       : marriage        =           1
    
    15._at       : IU0             =        .747
    
    16._at       : X011            =         2.6
    
    17._at       : X003            =       39.17
    
    ------------------------------------------------------------------------------
                 |            Delta-method
                 |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
             _at |
              1  |   .1633802    .005715    28.59   0.000     .1521791    .1745814
              2  |   .1801634   .0085627    21.04   0.000     .1633808    .1969459
              3  |   .1649903    .004526    36.45   0.000     .1561194    .1738612
              4  |   .1933135   .0172953    11.18   0.000     .1594153    .2272117
              5  |   .1599886   .0059154    27.05   0.000     .1483947    .1715825
              6  |   .1948554   .0189071    10.31   0.000     .1577982    .2319127
              7  |   .1625858   .0047734    34.06   0.000     .1532302    .1719415
              8  |   .2013719   .0107094    18.80   0.000     .1803818    .2223621
              9  |    .168024    .004607    36.47   0.000     .1589944    .1770536
             10  |   .1891139   .0139307    13.58   0.000     .1618103    .2164175
             11  |   .1613192   .0063993    25.21   0.000     .1487768    .1738616
             12  |   .1903685   .0158969    11.98   0.000     .1592111    .2215258
             13  |   .1510309   .0114899    13.14   0.000      .128511    .1735507
             14  |   .1742829   .0041136    42.37   0.000     .1662205    .1823454
             15  |   .1756855   .0039588    44.38   0.000     .1679264    .1834446
             16  |   .1724044   .0038844    44.38   0.000     .1647911    .1800177
             17  |    .171953   .0038933    44.17   0.000     .1643222    .1795839
    ------------------------------------------------------------------------------
    
    Predictive margins                              Number of obs     =      9,458
    Model VCE    : OIM
    
    Expression   : Pr(A170==8), predict(outcome (8))
    
    1._at        : quantX0472      =           0
    
    2._at        : quantX0472      =           1
    
    3._at        : quantX0473      =           0
    
    4._at        : quantX0473      =           1
    
    5._at        : quantX0474      =           0
    
    6._at        : quantX0474      =           1
    
    7._at        : relative2       =           0
    
    8._at        : relative2       =           1
    
    9._at        : relative3       =           0
    
    10._at       : relative3       =           1
    
    11._at       : relative4       =           0
    
    12._at       : relative4       =           1
    
    13._at       : marriage        =           0
    
    14._at       : marriage        =           1
    
    15._at       : IU0             =        .747
    
    16._at       : X011            =         2.6
    
    17._at       : X003            =       39.17
    
    ------------------------------------------------------------------------------
                 |            Delta-method
                 |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
             _at |
              1  |   .0772218   .0039081    19.76   0.000     .0695621    .0848816
              2  |   .1352447   .0073282    18.46   0.000     .1208816    .1496077
              3  |   .0852352   .0031768    26.83   0.000     .0790089    .0914615
              4  |   .1823037   .0143415    12.71   0.000     .1541949    .2104125
              5  |   .0678116   .0038742    17.50   0.000     .0602184    .0754048
              6  |   .2194487   .0162704    13.49   0.000     .1875592    .2513381
              7  |    .103373   .0038623    26.76   0.000      .095803    .1109431
              8  |   .0739286   .0078286     9.44   0.000     .0585848    .0892723
              9  |   .1034279   .0038076    27.16   0.000     .0959652    .1108906
             10  |    .065084   .0104739     6.21   0.000     .0445555    .0856125
             11  |   .1160519   .0054597    21.26   0.000     .1053511    .1267527
             12  |    .049786   .0099898     4.98   0.000     .0302064    .0693655
             13  |   .0811256   .0082655     9.81   0.000     .0649256    .0973257
             14  |   .0987434   .0031904    30.95   0.000     .0924903    .1049964
             15  |   .0951648   .0030102    31.61   0.000     .0892649    .1010648
             16  |   .0963744    .002998    32.15   0.000     .0904983    .1022504
             17  |   .0976228   .0030429    32.08   0.000     .0916589    .1035867
    ------------------------------------------------------------------------------
    
    Predictive margins                              Number of obs     =      9,458
    Model VCE    : OIM
    
    Expression   : Pr(A170==9), predict(outcome (9))
    
    1._at        : quantX0472      =           0
    
    2._at        : quantX0472      =           1
    
    3._at        : quantX0473      =           0
    
    4._at        : quantX0473      =           1
    
    5._at        : quantX0474      =           0
    
    6._at        : quantX0474      =           1
    
    7._at        : relative2       =           0
    
    8._at        : relative2       =           1
    
    9._at        : relative3       =           0
    
    10._at       : relative3       =           1
    
    11._at       : relative4       =           0
    
    12._at       : relative4       =           1
    
    13._at       : marriage        =           0
    
    14._at       : marriage        =           1
    
    15._at       : IU0             =        .747
    
    16._at       : X011            =         2.6
    
    17._at       : X003            =       39.17
    
    ------------------------------------------------------------------------------
                 |            Delta-method
                 |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
             _at |
              1  |   .0531288   .0030728    17.29   0.000     .0471063    .0591513
              2  |   .0747666   .0053458    13.99   0.000      .064289    .0852442
              3  |   .0542097   .0026107    20.76   0.000     .0490928    .0593265
              4  |   .1063096   .0111136     9.57   0.000     .0845275    .1280918
              5  |   .0353079   .0031324    11.27   0.000     .0291685    .0414472
              6  |   .1528295   .0137302    11.13   0.000     .1259188    .1797402
              7  |   .0631237   .0029141    21.66   0.000     .0574122    .0688352
              8  |   .0542482   .0057572     9.42   0.000     .0429644     .065532
              9  |   .0668948   .0030564    21.89   0.000     .0609045    .0728852
             10  |   .0302351   .0081632     3.70   0.000     .0142355    .0462347
             11  |   .0694173   .0044273    15.68   0.000     .0607399    .0780947
             12  |   .0382753   .0086517     4.42   0.000     .0213182    .0552324
             13  |   .0451989   .0067103     6.74   0.000      .032047    .0583507
             14  |   .0636268   .0026317    24.18   0.000     .0584688    .0687847
             15  |   .0623231   .0025263    24.67   0.000     .0573716    .0672746
             16  |   .0615617   .0024555    25.07   0.000      .056749    .0663744
             17  |    .062173   .0024908    24.96   0.000     .0572911    .0670549
    ------------------------------------------------------------------------------
    
    Predictive margins                              Number of obs     =      9,458
    Model VCE    : OIM
    
    Expression   : Pr(A170==10), predict(outcome (10))
    
    1._at        : quantX0472      =           0
    
    2._at        : quantX0472      =           1
    
    3._at        : quantX0473      =           0
    
    4._at        : quantX0473      =           1
    
    5._at        : quantX0474      =           0
    
    6._at        : quantX0474      =           1
    
    7._at        : relative2       =           0
    
    8._at        : relative2       =           1
    
    9._at        : relative3       =           0
    
    10._at       : relative3       =           1
    
    11._at       : relative4       =           0
    
    12._at       : relative4       =           1
    
    13._at       : marriage        =           0
    
    14._at       : marriage        =           1
    
    15._at       : IU0             =        .747
    
    16._at       : X011            =         2.6
    
    17._at       : X003            =       39.17
    
    ------------------------------------------------------------------------------
                 |            Delta-method
                 |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
    -------------+----------------------------------------------------------------
             _at |
              1  |   .1364811   .0056093    24.33   0.000      .125487    .1474751
              2  |   .0975743   .0067594    14.44   0.000     .0843261    .1108225
              3  |   .1259752   .0042673    29.52   0.000     .1176114     .134339
              4  |   .1007457   .0122556     8.22   0.000     .0767252    .1247663
              5  |   .1198535   .0059102    20.28   0.000     .1082697    .1314372
              6  |   .1276852   .0138983     9.19   0.000      .100445    .1549253
              7  |   .1180815   .0039366    30.00   0.000      .110366    .1257971
              8  |   .1389333   .0103927    13.37   0.000     .1185641    .1593026
              9  |   .1183194   .0038803    30.49   0.000      .110714    .1259247
             10  |   .1452532   .0142847    10.17   0.000     .1172557    .1732508
             11  |   .1132043   .0052972    21.37   0.000      .102822    .1235866
             12  |   .1480418   .0149514     9.90   0.000     .1187377     .177346
             13  |   .1337301   .0110354    12.12   0.000     .1121012     .155359
             14  |   .1206428   .0035626    33.86   0.000     .1136603    .1276254
             15  |     .11949   .0034464    34.67   0.000     .1127352    .1262448
             16  |   .1219906   .0034034    35.84   0.000     .1153201    .1286611
             17  |   .1220141   .0034341    35.53   0.000     .1152835    .1287448
    ------------------------------------------------------------------------------

    Comment


    • #17
      I don't know what you changed but you have it running. As to whether to set the contnuus variables at their means or some other value, see

      https://www3.nd.edu/~rwilliam/xsoc73994/Margins01.pdf

      I still don't see much point in running your model as is if you aren't going to impose any constraints on the variables. Consider adding the autofit option.
      -------------------------------------------
      Richard Williams, Notre Dame Dept of Sociology
      StataNow Version: 19.5 MP (2 processor)

      EMAIL: [email protected]
      WWW: https://www3.nd.edu/~rwilliam

      Comment


      • #18
        Sir, Thank you so much for the guidance. I will incorporate the autofit option. Once again thank you so much.

        Comment


        • #19
          Sir Richard Williams, I am using a xtoprobit command and after that I am calculating margins, it is showing error "discontinuous region with missing value". I am using the following command:
          Code:
          xtoprobit A170 LnNSDPpcC X003 X011 marriage employ gender dharm1 dharm2 dharm3  health2 health3 edu2 edu3 edu4 class1 class2 So2 No2 BOD formalscindex2 formalscindex3 informalSc2 informalSc3
          Code:
           margins, dydx(*)
          I have run the model with different permutation and combination and I have found this particular error is coming when I am including No2 variable. No2 is a continuous variable and one of the important variable for my study. I have deleted all the missing value but if I am including this No2 variable the error is persisting. Is there any way I can sort out this issue or dropping this variable is the only choice left for me. Kindly help me.

          Comment


          • #20
            Hi Neeraz. This appears to be a new topic so you may want to start a new thread. My guess is you'd have to look more carefully at the problematic variable, e.g. maybe it has very little variability or is miscoded or is highly correlated with other variables.

            My generic advice for dealing with weird problems is on pp. 2-3 of

            https://www3.nd.edu/~rwilliam/xsoc73994/L02.pdf
            -------------------------------------------
            Richard Williams, Notre Dame Dept of Sociology
            StataNow Version: 19.5 MP (2 processor)

            EMAIL: [email protected]
            WWW: https://www3.nd.edu/~rwilliam

            Comment


            • #21
              Sir, Thank you so much for reply. I have used the difficult command and it's work. I had posted the new thread but I did not got the response. Once again thank you so much for your help.

              Comment

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