# st: Mlogit with constraints

 From narazani To statalist@hsphsun2.harvard.edu Subject st: Mlogit with constraints Date Sun, 11 Dec 2005 19:12:25 +0100

```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?

I apologize for messing up the archives.

Hoping to get helped now,
Best

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 - [5]time = 0
( 5)  [3]cost1 - [5]cost1 = 0
( 6)  [3]_cons - [5]_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)

. predict p1 p2 p3 p4 p5  if e(sample)
(option pr assumed; predicted probabilities)
(69 missing values generated)

. 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

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```