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# st: hshaz interpretation of the unobserved heterogeneity parameters

 From Judit VALL CASTELLO To statalist@hsphsun2.harvard.edu Subject st: hshaz interpretation of the unobserved heterogeneity parameters Date Wed, 28 Sep 2011 12:05:38 +0200 (CEST)

```Dear all,

I am fitting hshaz for the first time and I have problems with interpreting the coefficients and the unobserved heterogeneity parameters.
This is the output that I get fitting a model with flexible baseline hazard for each year (15 years) and ommiting one of the dummies instead of the constant term (only showing the estimation of the model with UH):

Iteration 0:   log likelihood =  -13360.79  (not concave)
Iteration 1:   log likelihood = -13141.202  (not concave)
Iteration 2:   log likelihood = -13135.162  (not concave)
Iteration 3:   log likelihood = -13133.705  (not concave)
Iteration 4:   log likelihood = -13132.713  (not concave)
Iteration 5:   log likelihood = -13132.384
Iteration 6:   log likelihood = -13131.923  (not concave)
Iteration 7:   log likelihood = -13131.886
Iteration 8:   log likelihood = -13131.497
Iteration 9:   log likelihood = -13131.329
Iteration 10:  log likelihood = -13131.238
Iteration 11:  log likelihood = -13131.227
Iteration 12:  log likelihood = -13131.227

Discrete time PH model, with discrete mixture     Number of obs   =     101139
LR chi2()       =          .
Log likelihood = -13131.227                       Prob > chi2     =          .

------------------------------------------------------------------------------
employment |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
hazard       |
d2 |   2.202138   .0835986    26.34   0.000     2.038287    2.365988
d3 |   1.817322   .0942435    19.28   0.000     1.632608    2.002036
d4 |   1.559679   .1042669    14.96   0.000      1.35532    1.764039
d5 |   1.326683   .1144048    11.60   0.000     1.102453    1.550912
d6 |   .9699759   .1286689     7.54   0.000     .7177896    1.222162
d7 |   .9914302   .1361961     7.28   0.000     .7244907     1.25837
d8 |   .5558144   .1620074     3.43   0.001     .2382858     .873343
d9 |   .5627367   .1741448     3.23   0.001     .2214191    .9040543
d10 |   .3581391   .2022719     1.77   0.077    -.0383066    .7545848
d11 |   .3722488   .2234632     1.67   0.096    -.0657311    .8102287
d12 |   .4746029   .2471491     1.92   0.055    -.0098004    .9590061
d13 |   .3426948   .3125202     1.10   0.273    -.2698336    .9552232
d14 |  -.5513795   .5904984    -0.93   0.350    -1.708735    .6059762
d15 |   .3091984   .5912455     0.52   0.601    -.8496214    1.468018
fem |  -.6304255   .0524701   -12.01   0.000     -.733265   -.5275859
agedisabil~y |  -.0880126   .0030303   -29.04   0.000    -.0939519   -.0820732
totaldis |  -3.095721   .2213199   -13.99   0.000      -3.5295   -2.661942
profcateg2 |   .1461056   .0541343     2.70   0.007     .0400044    .2522068
profcateg3 |   .1733369   .0991126     1.75   0.080    -.0209203    .3675941
lnbasereg |   .2052545   .0567508     3.62   0.000      .094025    .3164839
pensln |  -.3220117   .0415467    -7.75   0.000    -.4034417   -.2405816
selflj2 |  -.0656422   .0537471    -1.22   0.222    -.1709846    .0397002
totempspe |   .0086617   .0009305     9.31   0.000      .006838    .0104854
ur |   -.033141   .0036001    -9.21   0.000    -.0401971    -.026085
_cons |   1.568922   .5036847     3.11   0.002     .5817179    2.556126
-------------+----------------------------------------------------------------
m2           |
_cons |    .920075   .2086793     4.41   0.000      .511071    1.329079
-------------+----------------------------------------------------------------
logitp2      |
_cons |  -.1763005   .8397107    -0.21   0.834    -1.822103    1.469502
-------------+----------------------------------------------------------------
Prob. Type 1 |   .5439613   .2083048     2.61   0.009     .1870183    .8608183
Prob. Type 2 |   .4560387   .2083048     2.19   0.029     .1391817    .8129817
------------------------------------------------------------------------------
Note: m1 = 0

The prob.Type 1 and 2 is the probability that someone in my sample belogs to the first (or second) type of individuals, but how should I interpret the m2 and the logitp2?

Also, how can I translate the coefficients (for example of the ur) into marginal effects or probabilities?