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From |
"Philip Ender" <ender97@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: poisson exposure problem |

Date |
Fri, 28 Mar 2008 16:37:10 -0700 |

Thanks to Carlo Lazzaro, Steven Samuels and Austin Nichols for comments. There don't seem to be inflated zero's. The distribution of the response variable follows a poisson distribution very closely. The counts were obtained from 1-meter square seed traps in different locations over the same time period. I gather from the student that the zero counts on the response variable were expected (there were other zeros as well) but that the zeros on the exposure were not anticipated. I like the idea of using the total seed count as a predictor. I will try out some of the other suggestions as well. -- Phil Ender Statistical Consulting Group UCLA Academic Technology Services ------- Carlo Lazzaro-------------- isn't this a mission for -help zip-? -------Steven Samuels------------- Some thoughts: I'd want to know what the 'observations' are: different times, areas? Although posited as a Poisson problem, this is a problem in predicting proportions between 0 & 1, since the student is willing to condition on 'exposure' equal to the number of seeds of all plants. I would suggest a random effects binomial regression model like -xtmelogit- or -glogit-. In either case, the cases with no seeds cannot be used. I'd recommend a preliminary analysis to predict the total number of seeds with one of Stata's count procedures, including -xtmepoisson- , -xtnbreg- . This analysis could separate out out influences on total numbers of seeds from influences on the proportion belonging to the species of interest. This preliminary analysis could predict the zero counts of seeds. A more advanced model- could predict the relative and absolute numbers of more than two species, distinguishing between separate and common influences. To me another question is: why expect a Poisson distribution at all? If seeds are generated 'locally', then there will be an unmeasured source of variation within areas, namely the number of plants of each species. --------Austin Nichols------------------ I think this is fine to model using a Poisson regression, though a fractional logit (Papke and Wooldridge 1996) and other models are also possibilities. But I think the cases with zero exposure supply no information, in the context of the model specified, and are rightly dropped. These are like cases with no observations, and can therefore supply no information to form estimates about the rate at which events happen. Leslie E. Papke and Jeffrey M. Wooldridge. 1996. "Econometric Methods for Fractional Response Variables with an Application to 401(k) Plan Participation Rates." Journal of Applied Econometrics, 11(6): 619-632. [see also http://www.nber.org/papers/t0147.pdf] --------posted 3/27/08---------------------- 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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