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Subject: st: poisson exposure problem


From   [email protected]
To   [email protected]
Subject   Subject: st: poisson exposure problem
Date   Fri, 28 Mar 2008 11:43:49 EDT

I've never seen such a data set. Strange. The exposure variable typically  
gives us the time frame or area/group in which counts occur; ie the model with  
exposure tells us, for each covariate pattern, how many counts are in a given  
range of time or area/group. If the time or area/group is 0 (exposure==0), 
then  there can be no meaningful counts. I cannot see how observations 
associated with  an exposure of 0 can be kept in the model. 
 
Try modeling a Poisson or negative binomial model with a zero exposure.  I'll 
bet that the algorithm will not let you proceed. I suspect that the  student 
does not know the meaning of exposure, and needs to recode the data so  that 
it reflects a meaningful relationship. Maybe its too early in the morning,  and 
I'm missing something. But I don't think so. 

Joseph Hilbe
 
====================
A student comes in with a poisson model.  The  response variable is the
number of seeds of a certain species.  There is  an exposure variable
which is the total seeds of all species.  The  problem is that there
are six exposure values of zero.  There are three  other predictor
variables and 72 total observations.  Is there any way  of dealing with
this problem other than dropping those six values?  Any  suggestions?

- --
Phil Ender
Statistical Consulting Group
UCLA  Academic Technology Services
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