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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: checking over dispersion in XTPOISSON |

Date |
Fri, 6 Jan 2012 10:24:48 +0000 |

I mentioned -xtnbreg- because no one had mentioned it. I have never used it. It should be easy enough to check whether a negative binomial model gives much better fit to the data than a Poisson model. For example, examine observed and fitted for both models. I don't know whether that can be encapsulated in a single test or figure of merit, if that is what you seek. Nick On Fri, Jan 6, 2012 at 10:12 AM, Rajaram Subramanian Potty <rajara999@gmail.com> wrote: > The out put from "xtnbreg" gives r and s. But how to check whether > there is overdispersion from r and s. Manual did not explaing how to > check overdispersion using "xtnbreg". But for "nbreg" the alpha value > will indicate whether there is overdispersion. > > Thanks and regards, > > RAJARAM. S > > On Fri, Jan 6, 2012 at 2:19 PM, Nick Cox <njcoxstata@gmail.com> wrote: >> Also, Stata [sic] has -xtnbreg-. >> >> Nick >> >> On Fri, Jan 6, 2012 at 5:58 AM, Muhammad Anees <anees@aneconomist.com> wrote: >> >>> Extending my previous discussion, then >>> >>> if it is over or underdispersed. Then apply the cluster option as >>> shows above. See if the standard errors change much. If change, then >>> there is not overdispersion >> >> On Fri, Jan 6, 2012 at 10:45 AM, Rajaram Subramanian Potty >> >>>> Thanks for the suggestion >>>> >>>> I understand from the STATA manual that negative binomial regression >>>> can be used to check overdispersion. I am nost sure whether same can >>>> be used if one has panel data. Can I use negative binomial regression >>>> with the cluster option to test the over dispersion in the present >>>> problem. In the cluster I will consider the panel identifier. >> >> On Thu, Jan 5, 2012 at 1:59 PM, Muhammad Anees <anees@aneconomist.com> wrote: >> >>>>> The following quotation from my discussion with Jo Hilbe describes and >>>>> answers many such problems. >>>>> >>>>> glm panelcount x1 x2 x3, fam(poi) >>>>> glm panelcount x1 x2 x3, fam(poi) cluster(panelvar) >>>>> glm panelcount x1 x2 x3, fam(nb ml) >>>>> glm panelcount x1 x2 x3, fam(nb ml) cluster(panelvar) >>>>> >>>>> where panelvar is your panel variable, eg id and x1-x3 are predictors. >>>>> >>>>> Check the Pearson dispersion statistic for the Poisson model. If it is >>>>> above 1.0 the model is Poisson overdispersed. >> >> Thu, Jan 5, 2012 at 1:21 PM, Rajaram Subramanian Potty >> >>>>>> I would like to know how one should check for overdispersion in a >>>>>> model fitted using "xtpoisson". If one noticed overdispersion how to >>>>>> correct it or which is the alternative analysis. * * 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: checking over dispersion in XTPOISSON***From:*Rajaram Subramanian Potty <rajara999@gmail.com>

**Re: st: checking over dispersion in XTPOISSON***From:*Muhammad Anees <anees@aneconomist.com>

**Re: st: checking over dispersion in XTPOISSON***From:*Rajaram Subramanian Potty <rajara999@gmail.com>

**Re: st: checking over dispersion in XTPOISSON***From:*Muhammad Anees <anees@aneconomist.com>

**Re: st: checking over dispersion in XTPOISSON***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: checking over dispersion in XTPOISSON***From:*Rajaram Subramanian Potty <rajara999@gmail.com>

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