In the two models below I'm using the same data. The first run is a Poisson
analysis, the second a negative binomial (B1 in Cameron and Trivedi
parlance).
Now as far as I know my betas should bethe same in both models. the only
thing that should change are SEs and p-values.
So why am I getting different betas.
What am I doing wrong here?
. poisson alfil1a group, expos(filter1)
Poisson regression Number of obs =
34
LR chi2(1) =
34.27
Prob > chi2 =
0.0000
Log likelihood = -341.07851 Pseudo R2 =
0.0478
----------------------------------------------------------------------------
--
alfil1a | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
grouping | .6831764 .1200077 5.69 0.000 .4479656
.9183873
_cons | -2.313518 .2073 -11.16
0.000 -2.719819 -1.907218
filter1 | (exposure)
----------------------------------------------------------------------------
--
. nbreg alfil1a group, expos(filter1) disp(const)
Negative binomial (constant dispersion) Number of obs =
34
LR chi2(1) =
0.73
Prob > chi2 =
0.3932
Log likelihood = -116.99016 Pseudo R2 =
0.0031
----------------------------------------------------------------------------
--
alfil1a | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+--------------------------------------------------------------
--
grouping | .2718017 .3178545 0.86 0.392 -.3511816
.8947851
_cons | -1.649793 .5384459 -3.06
0.002 -2.705127 -.5944583
filter1 | (exposure)
-------------+--------------------------------------------------------------
--
/lndelta | 2.506257 .3217237 1.87569
3.136824
-------------+--------------------------------------------------------------
--
delta | 12.25896 3.943999 6.525323
23.03061
----------------------------------------------------------------------------
--
Likelihood ratio test of delta=0: chibar2(01) = 448.18 Prob>=chibar2 =
0.000
_______________________________________________________________________
Kieran McCaul
School of Population Health
University of Western Australia
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Australia
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