Publication style tables for mlogit models

[Schyler Cole]

Hello!

I want to make publication-style tables for mlogit models. I tried using asdoc with the nest option, but I get the attached error when trying to append the second model.
I'm not sure what the relevant information is that I need to provide regarding the error, but if you could help with the error and/or suggest a more appropriate way to create publication-style tables for mlogit models, I would appreciate it.

Thank you in advance!

[Andrew Musau]

Try estout from SSC.

ssc install estout, replace

Here is an example:

webuse sysdsn1, clear
eststo m1: mlogit insure age male nonwhite i.site
*LOOK AT HOW EQUATIONS ARE LABELED
mat l e(b)

*EXPORT TO WORD EXCLUDING BASE EQUATION ("Indeminty:" HERE)
esttab m1 using myfile.rtf, unstack nobaselevels drop(Indemnity:) nonum mlab(none) ///
stats(N r2_p, label("Observations" "Pseudo R2")) replace

Res.:

OUTPUT

. eststo m1: mlogit insure age male nonwhite i.site

Iteration 0:   log likelihood = -555.85446  
Iteration 1:   log likelihood = -534.67443  
Iteration 2:   log likelihood = -534.36284  
Iteration 3:   log likelihood = -534.36165  
Iteration 4:   log likelihood = -534.36165  

Multinomial logistic regression                 Number of obs     =        615
                                                LR chi2(10)       =      42.99
                                                Prob > chi2       =     0.0000
Log likelihood = -534.36165                     Pseudo R2         =     0.0387

------------------------------------------------------------------------------
      insure |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
Indemnity    |  (base outcome)
-------------+----------------------------------------------------------------
Prepaid      |
         age |   -.011745   .0061946    -1.90   0.058    -.0238862    .0003962
        male |   .5616934   .2027465     2.77   0.006     .1643175    .9590693
    nonwhite |   .9747768   .2363213     4.12   0.000     .5115955    1.437958
             |
        site |
          2  |   .1130359   .2101903     0.54   0.591    -.2989296    .5250013
          3  |  -.5879879   .2279351    -2.58   0.010    -1.034733   -.1412433
             |
       _cons |   .2697127   .3284422     0.82   0.412    -.3740222    .9134476
-------------+----------------------------------------------------------------
Uninsure     |
         age |  -.0077961   .0114418    -0.68   0.496    -.0302217    .0146294
        male |   .4518496   .3674867     1.23   0.219     -.268411     1.17211
    nonwhite |   .2170589   .4256361     0.51   0.610    -.6171725     1.05129
             |
        site |
          2  |  -1.211563   .4705127    -2.57   0.010    -2.133751   -.2893747
          3  |  -.2078123   .3662926    -0.57   0.570    -.9257327     .510108
             |
       _cons |  -1.286943   .5923219    -2.17   0.030    -2.447872   -.1260134
------------------------------------------------------------------------------

. *LOOK AT HOW EQUATIONS ARE LABELED
. mat l e(b)

e(b)[1,21]
     Indemnity:  Indemnity:  Indemnity:  Indemnity:  Indemnity:  Indemnity:  Indemnity:    Prepaid:    Prepaid:    Prepaid:
             o.          o.          o.         1b.         2o.         3o.          o.                                    
           age        male    nonwhite        site        site        site       _cons         age        male    nonwhite
y1           0           0           0           0           0           0           0  -.01174499   .56169343   .97477679

       Prepaid:    Prepaid:    Prepaid:    Prepaid:   Uninsure:   Uninsure:   Uninsure:   Uninsure:   Uninsure:   Uninsure:
            1b.          2.          3.                                                         1b.          2.          3.
          site        site        site       _cons         age        male    nonwhite        site        site        site
y1           0   .11303586  -.58798794    .2697127  -.00779614   .45184964   .21705895           0  -1.2115627  -.20781232

      Uninsure:
              
         _cons
y1   -1.286943

EXPORTED TABLE

--------------------------------------------
                  Prepaid        Uninsure  
--------------------------------------------
age               -0.0117        -0.00780  
                  (-1.90)         (-0.68)  

male                0.562**         0.452  
                   (2.77)          (1.23)  

nonwhite            0.975***        0.217  
                   (4.12)          (0.51)  

2.site              0.113          -1.212*  
                   (0.54)         (-2.57)  

3.site             -0.588**        -0.208  
                  (-2.58)         (-0.57)  

_cons               0.270          -1.287*  
                   (0.82)         (-2.17)  
--------------------------------------------
Observations          615                  
Pseudo R2          0.0387                  
--------------------------------------------
t statistics in parentheses
* p<0.05, ** p<0.01, *** p<0.001