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From |
David Greenberg <dg4@nyu.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Autocorrelation in Poisson regression |

Date |
Thu, 07 Aug 2008 17:44:51 -0400 |

In the Poisson regression model, the measured independent variables provide a source of heterogeneity. The residuals from the estimation of such a model are assumed to be independent, and the test for autocorrelation of residuals is a test of that assumption. David Greenberg, Sociology Department, New York University ----- Original Message ----- From: Kieran McCaul <kamccaul@meddent.uwa.edu.au> Date: Thursday, August 7, 2008 5:18 pm Subject: st: RE: Autocorrelation in Poisson regression To: statalist@hsphsun2.harvard.edu > >>>I have tested for overdispersion and this is not a problem. > I'm always a bit wary of tests of overdispersion, mainly because I don't > have a clear idea of what the power of this test is. In other words, > how much overdispersion would there have to be before the test was > significant. > > >>>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. > > Well there must be some heterogeneity, otherwise there would be no point > in to modelling the data. > > When I'm modelling disease incidence in a cohort of people, I'm assuming > that everyone in the cohort is at risk of the disease, but I'm not > assuming that they are at the same level of risk (no heterogeneity). > I'm assuming that there is heterogeneity in risk and I'm looking for > factors that explain this - factors associated with an increase or > decrease in risk. > > >>>As for Stas's comments, I wholeheartedly agree that the reviewer in > question is not much of a reviewer. > > I publish in medical journals and it is still the case that many medical > journals do not employ statistical reviewers. Consequently you can get > reviewers comments on the statistical analysis that are idiotic or > frankly bizarre. Often my colleagues (medical doctors) will want me to > simply do what the reviewer wants in order to get the paper published > thus turning a good paper into a bad paper (I wonder how often this > happens), whereas my response is to say "No, the reviewer is an idiot > and it is our obligation to point this out to them". Heated discussions > usually follow. > > Without knowing exactly what your data looks like, it's difficult to > give you any more advice, but checking the residuals along the lines > that David suggested should enable you to check for autocorrelation. > > > ______________________________________________ > Kieran McCaul MPH PhD > WA Centre for Health & Ageing (M573) > University of Western Australia > Level 6, Ainslie House > 48 Murray St > Perth 6000 > Phone: (08) 9224-2140 > Phone: -61-8-9224-2140 > email: kamccaul@meddent.uwa.edu.au > http://myprofile.cos.com/mccaul > _______________________________________________ > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Antonio Silva > Sent: Thursday, 7 August 2008 5:01 AM > To: statalist@hsphsun2.harvard.edu > Subject: st: Autocorrelation in Poisson regression > > > 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/ > > > > * > * 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/ * * 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/

**References**:**st: Autocorrelation in Poisson regression***From:*Antonio Silva <asilva100@live.com>

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

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