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st: Nlogit Choice Model in STATA 10


From   Isaak Bergmann <Isaak_Bergmann@web.de>
To   statalist@hsphsun2.harvard.edu
Subject   st: Nlogit Choice Model in STATA 10
Date   Thu, 16 Aug 2007 19:20:27 +0200

Dear all, 
I'm using STATA10 and have problems with the nlogit command. I kindly ask for your help: 
My data comes from a choice experiment, in which subjects were asked to choose between two doctors (described in terms of gender and age) or to "opt-out", that is, chose neither of the two. I want to model this data as a nested logit model in which the choice among alternative doctors is nested within the choice to see a doctor at all. 

I created an dummy variable "nodoc" that indicates whether subjects choose a doctor or not (the nest). The data is organized as follows: 

Id      Alt  Gender 	Age 	Choice inc     educ    nodoc 
1       1       -1      25   	0       1       5       0 
1       2       1       45    0       1       5       0 
1       3       0       0     1       1       5       1 
2       1       -1      60    1       4       1       0 
2       2       -1      45    0       4       1       0 
2       3       0       0     0       4       1       1 
3       1       1       45    0       2       3       0 
3       2       -1      25    1       2       3       0       
3       3       0       0     0       2       3       1 

My command in STATA10 is: 
. nlogitgen nodoc = alt(no:1 | 2, yes: 3) 
. nlogit Choice Gender Age || nodoc: inc educ || alt:, noconstant case(id) 

STATA returns 
note: branch 2 of level 1 is degenerate and the associated dissimilarity parameter ([yes_tau]_cons) is not defined; 
  
Can someone please help me to understand: 
- I really wonder whether I specified the code correctly to represent my model? 
- How to interpret the above return message? 
- And does that explain why there are only dots in the SE of the IV value? 

I tried to figure it out, but all examples in the manuals etc. are structurally different (the nest is no opt-out as in my model). 

Thank you very much in advance for your help! 
Isaak 

RUM-consistent nested logit regression         Number of obs      =        774 
Case variable: id                              Number of cases    =        258 

Alternative variable: alt                      Alts per case: min =          3 
                                                              avg =        3.0 
                                                              max =          3 

                                                  Wald chi2(5)    =      77.80 
Log likelihood = -210.15028                       Prob > chi2     =     0.0000 

------------------------------------------------------------------------------ 
      choice |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval] 
-------------+---------------------------------------------------------------- 
alt          | 
      gender |   .6883889   .2263547     3.04   0.002     .2447419    1.132036 
         age |   .1485912   .1587822     0.94   0.349    -.1626163    .4597986 
------------------------------------------------------------------------------ 
nodoc equations 
------------------------------------------------------------------------------ 
no           | 
        inc  |     (base) 
        edu  |     (base) 
-------- ----+---------------------------------------------------------------- 
yes          | 
        inc  |   .0323411   .1466224     0.22   0.825    -.2550336    .3197158 
        edu  |  -.1373286    .169304    -0.81   0.417    -.4691584    .1945011 
------------------------------------------------------------------------------ 
dissimilarity parameters 
------------------------------------------------------------------------------ 
nodoc     |           
   /no_tau   |   1.089185   .3503095                      .4025913    1.775779 
     /yes_tau|          1          .                             .          . 
------------------------------------------------------------------------------ 
LR test for IIA (tau = 1):           chi2(1) =     0.07   Prob > chi2 = 0.7970 
------------------------------------------------------------------------------ 

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