st: Re: st. outreg and multinomial logit

["Alexander Nervedi" <alexnerdy@hotmail.com>]

Hi Daniel and Clive,

Thanks for your responses;

Daniel suggestion (attached below) works smoothly and i leanrt that outreg 
doesn't like spaces in value labels.

Clive's recommendation is also good. Though with a few dozen outreg commands 
to fix I will stay with outreg for now and try out the "estout" package.

Thanks again.


Recommended solutions:


make sure you don't have spaces in the value labels.

e.g., this will not work:
lab def mylab 1 "one two" 2 "three four"

But this will:
lab def mylab 1 "one_two" 2 "three_four"
(note the underscores!)

Hope that helps,
Daniel



> From: "Clive Nicholas" <Clive.Nicholas@newcastle.ac.uk>
> Reply-To: statalist@hsphsun2.harvard.edu
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: outreg and multinomial logit
> Date: Mon, 14 Mar 2005 02:26:01 -0000 (GMT)
>
> Alexander Nervedi wrote:
>
> > I have been trying to get outreg to work after a multi-nomial logit
> > estimation and outreg keeps balking.
> > So the ordered outcome variable has three scales .. None(0), Any(1), and
> > All(2); the base level is None. outreg keep complaing that "equation any
> > not
> > found"
> >
> > The comand I am using is :
> >
> > .mlogit y $x1 $x2, basecategory (0)
> > .outreg using mnl-model, 3aster bracket coefastr se replace  comma
> > equation Any not found
> >
> > My suspicion is that outred is looking to associate  values (SD, Z 
> value,
> > P
> > value, CI)  with Any when it appears in the table as a normal output of
> > the
> > mlogit command, and is protesting becuase there isnt any such values.
> >
> > A suggestion for a workaround would be really helpful.
>
> There are two solutions to this problem.
>
> Using -outreg-, one answer is:
>
> . outreg using "C:\DATA\mlogit.out", eform bdec(3) rdec(3) sigsymb(*,**)
>   coefastr se addstat(Model chi-square, e(chi2), df, e(df_m), Log
>   likelihood, e(ll), Pseudo R2, e(r2_p), N of observations, e(N))
>
> However, why not use Ben Jann's -estout-, downloadable from SSC, which, in
> the view of a growing number of Stata users (including myself) is
> superior. An example:
>
> . use http://www.stata-press.com/data/r8/sysdsn3.dta
> (Health insurance data)
>
> . mlogit insure age male nonwhite, basecat(1)
>
> Iteration 0:   log likelihood = -555.85446
> Iteration 1:   log likelihood = -545.60089
> Iteration 2:   log likelihood = -545.58328
> Iteration 3:   log likelihood = -545.58328
>
> Multinomial logistic regression                 Number of obs   =        
> 615
>                                                 LR chi2(6)      =      
> 20.54
>                                                 Prob > chi2     =     
> 0.0022
> Log likelihood = -545.58328                     Pseudo R2       =     
> 0.0185
> ----------------------------------------------------------------------------
>     insure |      Coef.   Std. Err.      z    P>|z|     [95% Conf. 
> Interval]
> -----------+----------------------------------------------------------------
> Prepaid    |
>        age |  -.0111915   .0060915    -1.84   0.066    -.0231305    
> .0007475
>       male |   .5739825   .2005221     2.86   0.004     .1809665    
> .9669985
>   nonwhite |   .7312659    .218978     3.34   0.001      .302077    
> 1.160455
>      _cons |   .1567003   .2828509     0.55   0.580    -.3976773    
> .7110778
> -----------+----------------------------------------------------------------
> Uninsure   |
>        age |  -.0058414   .0114114    -0.51   0.609    -.0282073    
> .0165245
>       male |   .5102237   .3639793     1.40   0.161    -.2031626     
> 1.22361
>   nonwhite |    .433314   .4106255     1.06   0.291    -.3714972    
> 1.238125
>      _cons |  -1.811165   .5348606    -3.39   0.001    -2.859473   
> -.7628577
> ----------------------------------------------------------------------------
> (Outcome insure==Indemnity is the comparison group)
>
> . tab insure
>
>      insure |      Freq.     Percent        Cum.
> ------------+-----------------------------------
>   Indemnity |        294       47.73       47.73
>     Prepaid |        277       44.97       92.69
>    Uninsure |         45        7.31      100.00
> ------------+-----------------------------------
>       Total |        616      100.00
>
> . ereturn list
>
> scalars:
>                  e(N) =  615
>               e(ll_0) =  -555.8544590054535
>                 e(ll) =  -545.5832760024657
>               e(df_m) =  6
>               e(chi2) =  20.54236600597551
>               e(r2_p) =  .0184781876561091
>            e(basecat) =  1
>           e(ibasecat) =  1
>              e(k_cat) =  3
>
> macros:
>             e(depvar) : "insure"
>                e(cmd) : "mlogit"
>           e(crittype) : "log likelihood"
>            e(predict) : "mlogit_p"
>            e(eqnames) : "`"Prepaid"' `"Uninsure"'"
>           e(chi2type) : "LR"
>
> matrices:
>                  e(b) :  1 x 8
>                  e(V) :  8 x 8
>                e(cat) :  1 x 3
>
> functions:
>             e(sample)
>
> . est store model
>
> . estout model, stats(r2_p chi2 N, labels("Pseudo R-squared" "Model
> chi-square" "N")) cells(b(star fmt(%9.2
> > f)) t(par)) varwidth(30) modelwidth(10) label unstack
>
>                                      model
>                                    Prepaid        Uninsure
>                                        b/t             b/t
> NEMC (ISCNRD-IBIRTHD)/365.25         -0.01           -0.01
>                                    (-1.84)         (-0.51)
> NEMC PATIENT MALE                     0.57**          0.51
>                                     (2.86)          (1.40)
> nonwhite                              0.73***         0.43
>                                     (3.34)          (1.06)
> _cons                                 0.16           -1.81***
>                                     (0.55)         (-3.39)
> Pseudo R-squared                      0.02
> Model chi-square                     20.54
> N                                   615.00
>
> I hope that helps.
>
> CLIVE NICHOLAS        |t: 0(044)7903 397793
> Politics              |e: clive.nicholas@ncl.ac.uk
> Newcastle University  |http://www.ncl.ac.uk/geps
>
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