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Re: st: Constraints in mprobit
Emily Clough <[email protected]> inquired about using constraints with -mprobit-.
Here is an example:
. webuse sysdsn3
(Health insurance data)
. constraint 1 [Prepaid]age = [Uninsure]age
. mprobit insure age male nonwhite site2 site3, constraints(1)
Iteration 0: log likelihood = -538.23525
Iteration 1: log likelihood = -534.84715
Iteration 2: log likelihood = -534.72541
Iteration 3: log likelihood = -534.72518
Iteration 4: log likelihood = -534.72518
Multinomial probit regression Number of obs = 615
Wald chi2(9) = 39.87
Log likelihood = -534.72518 Prob > chi2 = 0.0000
( 1) [Prepaid]age - [Uninsure]age = 0
------------------------------------------------------------------------------
insure | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Prepaid |
age | -.0086853 .0049274 -1.76 0.078 -.0183428 .0009722
male | .4727575 .1716502 2.75 0.006 .1363293 .8091858
nonwhite | .8230185 .1976466 4.16 0.000 .4356384 1.210399
site2 | .101763 .1793036 0.57 0.570 -.2496655 .4531915
site3 | -.4916245 .1903472 -2.58 0.010 -.8646981 -.1185508
_cons | .1701124 .2662816 0.64 0.523 -.35179 .6920149
-------------+----------------------------------------------------------------
Uninsure |
age | -.0086853 .0049274 -1.76 0.078 -.0183428 .0009722
male | .3431705 .2429219 1.41 0.158 -.1329478 .8192887
nonwhite | .2643862 .2751911 0.96 0.337 -.2749785 .8037508
site2 | -.6934505 .2801114 -2.48 0.013 -1.242459 -.1444422
site3 | -.1884719 .2476282 -0.76 0.447 -.6738143 .2968706
_cons | -.8266897 .2948186 -2.80 0.005 -1.404523 -.2488559
------------------------------------------------------------------------------
(insure=Indemnity is the base outcome)
-Rich
[email protected]
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