Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Steve Samuels <sjsamuels@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Weights in Poisson regression |

Date |
Mon, 21 Oct 2013 20:51:52 -0400 |

I should have added the obvious, that for the Poisson problem, variance = expected count = Poisson parameter ("lambda") x population. SS Hideto: Your proposal would amount to double weighting. Maximum likelihood for Poisson regression is already equivalent to a generalized weighted least squares problem, with an analytic weight equal to the (estimated) variance of each observation. (Charnes et al., 1976). Note that county population (the exposure) is not the estimated variance and so would be suboptimal, even for the generalized regression. Reference: Charnes, Abraham, EL Frome, and Po-Lung Yu. 1976. The equivalence of generalized least squares and maximum likelihood estimates in the exponential family. Journal of the American Statistical Association 71, no. 353: 169-171. Steve sjsamuels@gmail.com On Oct 21, 2013, at 11:45 AM, Hideto Koizumi wrote: Hi, Does anyone know how to use population at the unit of analysis (e.g., population within each county of Connecticut) as weights in Poisson regression with an exposure variable (i.e., population of each county itself)? I wanted to simply use analytic weights but Poisson doesn't allow it due to its non-linear functional form. Anyone knows how to deal with this or knows any paper along this line? I would very much appreciate any input! Kindest regards, Hideto Koizumi ---------------------------------------- Innovations for Poverty Action World Bank * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/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/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: Weights in Poisson regression***From:*Hideto Koizumi <hkoizumi@poverty-action.org>

- Prev by Date:
**Re: st: Weights in Poisson regression** - Next by Date:
**Re: st: DEA Inefficiencies** - Previous by thread:
**Re: st: Weights in Poisson regression** - Next by thread:
**Re: st: Weights in Poisson regression** - Index(es):