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Re: st: no log likelihood ratio test after nbreg??


From   Jhilbe@aol.com
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: no log likelihood ratio test after nbreg??
Date   Thu, 10 Mar 2005 16:24:21 EST

The problem MAY be that the data is Poisson and  not overdispersed. I ran a 
test of Poisson simulated data, showing the fact that  there is no extra 
dispersion (that is why I used GLM rather than POISSON, which  does not give you 
many diagnostics). When I ran the same Poisson data using  NBREG the same 
problems that you mentioned appeared. The run can be found below.  

Note that you cannot put 0 in as the negative binomial ancillary  parameter 
using GLM. To get close you can do something like fam(nb 0.001).  

To check if your data is Poisson, run the data using the GLM command and  
check the dispersion. If it is 0, or very close, it is Poisson and that is  
likely the source of the problem. If it is greater than 0, then there is another  
problem. 

Joe Hilbe


. set obs 5000
obs was 0, now  5000

. gen x1=invnorm(uniform())

. gen  x2=invnorm(uniform())

. gen xb= 1 + 0.25*x1 - 0.75*x2

. gen  mu=exp(mu)
mu not found
r(111);

. gen mu=exp(xb)

. rndpoix  mu
( Generating  
.................................................................. )
Variable  xp created.


. glm mu x1 x2, fam(poi)  nolog


Generalized linear  models                           No. of obs      =       
5000
Optimization     : ML:  Newton-Raphson               Residual df     =       
4997
Scale parameter =          1
Deviance         =   4.97544e-11                     (1/df) Deviance =   
9.96e-15
Pearson           =   4.97669e-11                     (1/df) Pearson  =  
9.96e-15

Variance function: V(u) =  u                         [Poisson]
Link function    : g(u) =  ln(u)                     [Log]
Standard errors  : OIM

Log likelihood   =  -7317.213353                     AIC              =   
2.928085
BIC               =  -42560.41438

------------------------------------------------------------------------------
mu |      Coef.   Std.  Err.      z     P>|z|     [95% Conf.  Interval]
-------------+----------------------------------------------------------------
x1 |        .25    .0073479    34.02   0.000      .2355984     .2644016
x2  |       -.75   .0071323   -105.16   0.000     -.763979     -.736021
_cons  |          1    .0093382   107.09   0.000      .9816975     1.018302
------------------------------------------------------------------------------

.  nbreg mu x1 x2, nolog

Negative binomial  regression                       Number of obs   =        
5000
LR chi2(1)      =     8688.40
Prob > chi2     =     0.0000
Log  likelihood =  -7317.2134                        Pseudo R2       =      
0.3725

------------------------------------------------------------------------------
mu |      Coef.   Std.  Err.      z     P>|z|     [95% Conf.  Interval]
-------------+----------------------------------------------------------------
x1 |        .25    .0073479    34.02   0.000      .2355984     .2644016
x2  |       -.75   .0071323   -105.16   0.000     -.763979     -.736021
_cons  |          1    .0093382   107.09   0.000      .9816975     1.018302
-------------+----------------------------------------------------------------
/lnalpha |  -49.44545           .                              .            .
-------------+----------------------------------------------------------------
alpha |    3.36e-22           .                              .            .
------------------------------------------------------------------------------
Likelihood-ratio  test of alpha=0:  chibar2(01) =    0.00 Prob>=chibar2 =  
1.000






=============================================
In  a message dated 3/10/2005 1:40:51 PM US Mountain Standard Time, 
wying1@umbc.edu  writes:
Hi, all,

Usually there is a log likelikhood ratio test  statistics reported after a
negative binominal regression (I ran possion  regression first, and then
used 'nbreg' regression), and sometimes the Z  score for alpha is reported
too.  But in my case, I didn't see the ratio  reported after the
regression, and there is no z score for alpha.  Then  I tried to use
'lrtest' after the model, but it says
"lrtest not valid  after robust
specify force option to perform test anyway".

So I put  'force' in option, but it still didn't give me the result.

Can anybody  tell me what's going on?


Ying

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