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

 From Jeremy Bowling To Subject st: Re: Probability threshold for inclusion in ZINB count model Date Sat, 25 Feb 2012 15:23:28 -0600

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?
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-----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?
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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.
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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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