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Re: Subject: st: poisson exposure problem


From   "Austin Nichols" <austinnichols@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: Subject: st: poisson exposure problem
Date   Fri, 28 Mar 2008 12:04:55 -0400

Joseph Hilbe:
If you want to model the log fraction ln(y/ytotal) as a linear
function of X and y may be zero in your data, then a natural model is
 ln(y)=ln(ytotal)+Xb+e
or
 y=exp(ln(ytotal)+Xb+e)
or a Poisson regression of y on X with ytotal specified as exposure,
right?  But ytotal equal to zero means you cannot glean any
information from that case, since y must also be zero and the fraction
y/ytotal is undefined.

On Fri, Mar 28, 2008 at 12:43 PM,  <Jhilbe@aol.com> wrote:
> 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?
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