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From |
"Austin Nichols" <[email protected]> |

To |
[email protected] |

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, <[email protected]> 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? * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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