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Hi! I am working with panel data using Stata v7. In order to estimate the
probability of a site adopting a certain technology I am using hazard-rate
specifications.
Running the Lognormal regression (streg - dist(lognormal)) I seem to be
getting inverse results to the one's from Weibull (streg - dist(weibull))
(see results below).
Any pointers helping me understand the differences would be much
appreciated.
Thanks,
Benedikt.
174 . streg SC_locus_core_MS PC_Complex_Core PC_Complex_Peri_DA
PC_Complex_Peri_EA
SC_complex_change_lbase SC_arc_change SC_comp_change IND_G_Service
IND_G_Manu
f LOG_Emp IT_Intensity IT_Dev LOG_Server LOG_Ntwrk, dist(weibull)
...
Weibull regression -- log relative-hazard form
No. of subjects = 4989 Number of obs =
4989
No. of failures = 1713
Time at risk = 8356
LR chi2(14) =
5724.20
Log likelihood = -669.04683 Prob > chi2 =
0.0000
------------------------------------------------------------------------------
_t | Haz. Ratio Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------------
SC_locus_c~S | 7.67e+08 2.15e+11 0.07 0.942 2.83e-230
2.08e+24
PC_Complex~e | .9599559 .0263458 -1.49 0.136 .9096833
1.013007
PC_Comple~DA | .9993526 .0359207 -0.02 0.986 .9313719
1.072295
PC_Comple~EA | .9137738 .0218846 -3.77 0.000 .8718718
.9576895
SC_com~lbase | 1.054812 .1046327 0.54 0.591 .8684401
1.281181
SC_arc_cha~e | .6622062 .1495885 -1.82 0.068 .4253161
1.031038
SC_comp_ch~e | 1.035305 .0576771 0.62 0.533 .9282131
1.154753
IND_G_Serv~e | .9587473 .0807536 -0.50 0.617 .8128473
1.130835
IND_G_Manuf | .9930614 .0859979 -0.08 0.936 .8380368
1.176763
LOG_Emp | 1.038066 .0395384 0.98 0.327 .9633937
1.118526
IT_Intensity | 2.359489 .7533794 2.69 0.007 1.261919
4.411687
IT_Dev | .3495068 .2044643 -1.80 0.072 .1110442
1.100057
LOG_Server | .9911896 .0342807 -0.26 0.798 .9262273
1.060708
LOG_Ntwrk | .9999756 .0420713 -0.00 1.000 .9208255
1.085929
-------------+----------------------------------------------------------------
/ln_p | 1.154546 .0189167 61.03 0.000 1.11747
1.191622
-------------+----------------------------------------------------------------
p | 3.172583 .0600148 3.05711
3.292418
1/p | .3152006 .0059626 .3037282
.3271063
------------------------------------------------------------------------------
178 . streg SC_locus_core_MS PC_Complex_Core PC_Complex_Peri_DA
PC_Complex_Peri_EA
> SC_complex_change_lbase SC_arc_change SC_comp_change IND_G_Service
IND_G_Manu
> f LOG_Emp IT_Intensity IT_Dev LOG_Server LOG_Ntwrk, dist(lognormal)
failure _d: SC_locus_core_MS
analysis time _t: t
...
Log-normal regression -- accelerated failure-time form
No. of subjects = 4989 Number of obs =
4989
No. of failures = 1713
Time at risk = 8356
LR chi2(14) =
5515.62
Log likelihood = -542.18236 Prob > chi2 =
0.0000
------------------------------------------------------------------------------
_t | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------------
SC_locus_c~S | -2.784133 32.25093 -0.09 0.931 -65.99479
60.42653
PC_Complex~e | .0127173 .0086475 1.47 0.141 -.0042315
.0296661
PC_Comple~DA | -.0019033 .0114566 -0.17 0.868 -.0243578
.0205512
PC_Comple~EA | .0309895 .0076347 4.06 0.000 .0160258
.0459533
SC_com~lbase | -.0346015 .0338963 -1.02 0.307 -.1010369
.031834
SC_arc_cha~e | .1680083 .0770845 2.18 0.029 .0169254
.3190911
SC_comp_ch~e | -.0167932 .0202866 -0.83 0.408 -.0565542
.0229678
IND_G_Serv~e | .010267 .0278289 0.37 0.712 -.0442766
.0648106
IND_G_Manuf | -.0014168 .0289121 -0.05 0.961 -.0580834
.0552498
LOG_Emp | -.0113104 .0126465 -0.89 0.371 -.0360972
.0134764
IT_Intensity | -.2025714 .0977681 -2.07 0.038 -.3941934
-.0109494
IT_Dev | .2683782 .2040441 1.32 0.188 -.1315409
.6682973
LOG_Server | -.0004663 .0116539 -0.04 0.968 -.0233074
.0223749
LOG_Ntwrk | -.0021339 .014077 -0.15 0.880 -.0297244
.0254566
_cons | 2.876312 32.25103 0.09 0.929 -60.33455
66.08717
-------------+----------------------------------------------------------------
/ln_sig | -1.102429 .0170846 -64.53 0.000 -1.135914
-1.068944
-------------+----------------------------------------------------------------
sigma | .3320636 .0056732 .3211284
.3433711
------------------------------------------------------------------------------
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