# st: help to decide the model (poisson, nbreg, zip, zinb)

 From [email protected] To [email protected] Subject st: help to decide the model (poisson, nbreg, zip, zinb) Date Thu, 17 Mar 2005 15:01:01 -0500 (EST)

Dear STATAlist users,

I am trying to decide a model for a count dependent variable.  Based on
the summary and tabulation of my dependent variable, I found the evidence
of both overdisperson (variance > mean) and excess-zero (about 10 percent
is zero.)  I did some test about poisson, nbreg, zip and zinb but not sure
which model I should use.

Because pweight cannot be used for LR test, I took weight out in all
estimation II am not sure this will affect the result a lot).  The results
are:

1) poisson vs. nbreg: LR test of alpha=0:  chibar2(01) = 1047.64
Prob>=chibar2 = 0.000

2) poisson vs. zip (inflate all regressors used for estimating count
outcome):

log likelihood for poisson: -6214.3391
log likelihood for zip: -5168.085

3) poisson vs. zip (inflate part of the regressors used for estimating
count outcome):

log likelihood for poisson: -6214.3391
log likelihood for zip: -5257.639

(*** I don't understand the inflate option for ZIP/ZINB estimation.  STATA
help menu says inflate is not optional, and is used to "specify the
equation that determines whether the observed count is zero".  In my
model, there are X number of regressors  used to predict the outcome.
Shall I use all of them in the varlist of "inflate"?  I did test to use a
different cohort of regressors.  What should be put in the varlist of
"inflate" anyway"???)

4) nbreg vs. zinb (inflate part of the regressors used for estimating
count outcome):
Vuong Test of Zinb vs. Neg. Bin: Std. Normal  =    16.20 Pr> Z       =
0.0000

5) nbreg vs. zinb (inflate part of the regressors used for estimating
count outcome):
Vuong Test of Zinb vs. Neg. Bin: Std. Normal  =    10.70 Pr> Z       =
0.0000

I am lost in the jungle of the test.  Can anybody tell me how to decide
the model? Or should I conduct more test?

THanks a lot...........

Ying

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