st: Re: Probability threshold for inclusion in ZINB count model

[Jeremy Bowling <jlbkq6@mail.missouri.edu>]

According to http://www.ats.ucla.edu/stat/stata/output/Stata_zinb.htm, the 
"negative binomial model is generated predicting the counts for those 
[observations] who are not certain zeros."  Since the inflation/logit model 
determines whether or not an observation is a certain zero by probability, 
is there a probability threshold by which the observations are dropped? 
Or... are each unique observations' probabilities included in the negative 
binomial equation to control for the probability of being a certain zero, 
similar to when predicted counts are created in which probabilities are 
included in the equation.  Are observations dropped due to meeting a certain 
zero probability threshold, or is the negative binomial (count model) 
altered in some way to account for the probability that an observation may 
be a certain zero?  If there is a probability threshold and dropped 
observations in the count model, I would like to know.  If not, by what 
process does the zinb count model control for an observation being in the 
certain zero group?
-----Original Message----- 
From: Nick Cox
Sent: Saturday, February 25, 2012 4:46 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Probability threshold for inclusion in ZINB count model

Perhaps you explain what threshold you expect there to be on relation
to the manual entry on -zinb- or expand on how you think -zinb- should
use such a threshold.

Nick

On 25 Feb 2012, at 05:05, Jeremy Bowling <jlbkq6@mail.missouri.edu>
wrote:

> I am having a hard time finding the probability threshold that zinb  uses 
> to include/limit observations in the count model.  Is there a  set 
> probability threshold?  If not how do I find the threshold?
> After running zinb for a number of count models, I was seeking to  run a 
> simple logit model by dichotomizing my dv instead of having a  count.  I 
> would like to limit my observations by excluding those  that would be in 
> the certain zero group.  Of course the significance  of the logit 
> coefficients would be affected by the threshold I set  (which observations 
> are included). I would like to use the logit  model to seek not what 
> causes multiple occurrences (count) but what  factors lead to the 
> likelihood of an occurrence, from zero to one,  for those observations not 
> in the certain zero group.
> If there is not a set probability threshold or it can not be found,  what 
> would be the best probability to use?  50% cutoff? Mean  probability
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