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Re: st: Poisson and NBREG


From   Roger Harbord <Roger.Harbord@bristol.ac.uk>
To   statalist@hsphsun2.harvard.edu, Kieran McCaul <kieran@dph.uwa.edu.au>
Subject   Re: st: Poisson and NBREG
Date   Fri, 27 Sep 2002 11:04:16 +0100

I don't see why you think the betas should be the same.

You *would* get the same betas as the poisson model, but different SEs & p-values, if you fitted a quasi-likelihood poisson model with overdispersion, using -glm- with the option -scale(x2)- or -scale(dev)-.

But i don't believe the same is true for the negative binomial model. With such a large estimated value as 12 for the dispersion parameter delta, i'm not particularly surprised the betas are different to those obtained from a poisson model.

Roger.
----------------------------------------------------
Roger Harbord mailto:roger.harbord@bristol.ac.uk
Department of Social Medicine, University of Bristol


--On 27 September 2002 14:08 +0800 Kieran McCaul <kieran@dph.uwa.edu.au> wrote:


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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