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From | "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu> |
To | "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |
Subject | st: RE: Negative Binomial: Exposure vs. Offset |
Date | Tue, 4 May 2010 09:39:43 -0700 |
There basically is no difference. For exposure, you generally don't need to do anything. For offset, you usually take the log. This comes from modeling a Poisson regression in which you have a model Expectation=log(mu/exposure)=log(mu)-log(exposure)=X*beta Transposing you get log(mu)=log(exposure)+X*beta Tony Peter A. Lachenbruch Department of Public Health Oregon State University Corvallis, OR 97330 Phone: 541-737-3832 FAX: 541-737-4001 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Downey, Patrick Sent: Tuesday, May 04, 2010 9:35 AM To: statalist@hsphsun2.harvard.edu Subject: st: Negative Binomial: Exposure vs. Offset Hello, I'm using a negative binomial regression through the nbreg command in Stata to estimate crimes committed by a certain population. Different observations were "on the street" different lengths of time, so I want to account for that. I'm confused about the difference between the exposure option and the offset option. They appear to be doing the same thing. In the online documentation, it says: offset(varname) specifies that varname be included in the model with the coefficient constrained to be 1. exposure(varname) specifies a variable that reflects the amount of exposure over which the depvar events were observed for each observation; ln(varname) with coefficient constrained to be 1 is entered into the log-link function. Could someone please explain the difference between the two or send some documentation which formalizes the difference mathematically. Thanks, Mitch * * 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/