Thank you Richard. Here you have all constraints. There are 5 alternatives and 2
independent variables.
Looking forward to hearing to you
Best, edlira
. cons 1 [2=3]: time cost1 _cons
. cons 2 [3=4]: time cost1 _cons
. cons 3 [4=5]: time cost1 _cons
. mlogit av20 time cost1 if (location>1|location<6|location>6)&purpose==1,
cons(1-3) basecat(1)
Iteration 0: log likelihood = -479.42809
Iteration 1: log likelihood = -259.55111
Iteration 2: log likelihood = -256.78928
Iteration 3: log likelihood = -256.74805
Iteration 4: log likelihood = -256.74804
Multinomial logistic regression Number of obs = 324
LR chi2(-1) = 445.36
Prob > chi2 = .
Log likelihood = -256.74804 Pseudo R2 = 0.4645
( 1) [2]time - [3]time = 0
( 2) [2]cost1 - [3]cost1 = 0
( 3) [2]_cons - [3]_cons = 0
( 4) [3]time - [4]time = 0
( 5) [3]cost1 - [4]cost1 = 0
( 6) [3]_cons - [4]_cons = 0
( 7) [4]time - [5]time = 0
( 8) [4]cost1 - [5]cost1 = 0
( 9) [4]_cons - [5]_cons = 0
------------------------------------------------------------------------------
av20 | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
2 |
time | -.015983 .0048032 -3.33 0.001 -.0253971 -.006569
cost1 | -.0072383 .0013861 -5.22 0.000 -.009955 -.0045216
_cons | (dropped)
-------------+----------------------------------------------------------------
3 |
time | -.015983 .0048032 -3.33 0.001 -.0253971 -.006569
cost1 | -.0072383 .0013861 -5.22 0.000 -.009955 -.0045216
_cons | (dropped)
-------------+----------------------------------------------------------------
4 |
time | -.015983 .0048032 -3.33 0.001 -.0253971 -.006569
cost1 | -.0072383 .0013861 -5.22 0.000 -.009955 -.0045216
_cons | (dropped)
-------------+----------------------------------------------------------------
5 |
time | -.015983 .0048032 -3.33 0.001 -.0253971 -.006569
cost1 | -.0072383 .0013861 -5.22 0.000 -.009955 -.0045216
_cons | -.9755993 .3746739 -2.60 0.009 -1.709947 -.241252
------------------------------------------------------------------------------
(av20==1 is the base outcome)
sum p1-p5
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
p1 | 324 .7788082 .0914454 .5147507 .9966482
p2 | 324 .0655002 .0270792 .0009926 .1436939
p3 | 324 .0655002 .0270792 .0009926 .1436939
p4 | 324 .0655002 .0270792 .0009926 .1436939
p5 | 324 .0246914 .0102079 .0003742 .0541678
Scrive Richard Williams <[email protected]>:
> At 01:12 PM 12/11/2005, narazani wrote:
>
> >Dear all,
> >
> >I ran a multinomial logit with constraints and after that I used the command
> >"predict" to get the predicted probabilities. Stata result was: same
> >probabilities for 3 alternatives. Do you know any other command to predict
> the
> >probabilities when mlogit with constraints is used?
>
> Your results look quite peculiar. You specify constraints 1-3 but
> mlogit reports 9 constraints. The model has -1 degrees of
> freedom. Most of the constants are getting dropped.
>
> I suspect something is wrong with your model specification. We need
> to see more. Include the actual constraints commands you are
> using. I don't think the problem is with the predict command (which
> seems to be working correctly given the parameter estimates) but with
> the model itself.
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> FAX: (574)288-4373
> HOME: (574)289-5227
> EMAIL: [email protected]
> WWW (personal): http://www.nd.edu/~rwilliam
> WWW (department): http://www.nd.edu/~soc
>
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