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From |
Antonio Silva <asilva100@live.com> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: Autocorrelation in Poisson regression |

Date |
Wed, 6 Aug 2008 17:00:50 -0400 |

I am very impressed with the quality of responses I have gotten, thank you so much. In response, I have some comments and a few more questions. First, for Kieran, let me clarify: My dependent variable is “# of groups founded.” What this means is that for each year of the study (there are 40 years) there is a number, which represents the number of new organizations that come into existence in that year. So, for example, in 1965, 3 new groups were formed, in 1966, 2 new groups were formed, and in 1967 0 new groups were formed. So I have a number for each year in the period under study. Does that make sense? I have tested for overdispersion and this is not a problem. Second, in theory, there is an unlimited number of groups that could be formed in any given year, and thus there appears to be no heterogeneity of risk, if I understand that concept correctly. Of course, Kieran may feel that this particular count variable is simply not appropriate for use in Poisson regression, and I am curious to hear your thoughts on this. As for Stas’s comments, I wholeheartedly agree that the reviewer in question is not much of a reviewer. In fact, he/she even included in his/her review that he/she “was not sure if autocorrelation is even a problem in Poisson regression,” but that I should discuss it anyway. I have looked everywhere, and all the books and articles I read on Poisson basically imply (but do not explicitly state in a way that is quotable) what Kieran said—they say that if a process truly is Poisson, autocorrelation is not a problem. I think that Stas’ suggestion (that I include some language about there not being a standard test for autocorrelation) is a very good one, and may well work. Though I have to be honest, I am not sure what he means by discretization. Could you indulge me a little more and tell me what you mean by this? Finally, David, can you give me an idea of how I can generate the deviance residuals after using the Poisson command in Stata? I thought this option was available for other methods but not Poisson. And what should I look for in the correlogram? I am sorry to be asking such basic questions, but this is the first time I have ever used Poisson regression. And to be honest, the reason I am using it is because some other reviewer told me to because my dependent variable was a count variable it was the best way to go. Thanks again. This has been very helpful and useful to me. _________________________________________________________________ Your PC, mobile phone, and online services work together like never before. http://clk.atdmt.com/MRT/go/108587394/direct/01/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: RE: Autocorrelation in Poisson regression***From:*"Kieran McCaul" <kamccaul@meddent.uwa.edu.au>

**Re: st: Autocorrelation in Poisson regression***From:*"Stas Kolenikov" <skolenik@gmail.com>

**Re: st: Autocorrelation in Poisson regression***From:*David Greenberg <dg4@nyu.edu>

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