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From |
Willard Manning <w-manning@uchicago.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: negative binomial model - transformation |

Date |
Tue, 25 Mar 2003 17:05:17 -0600 |

Maureen

If you use the default link function (log) for the negative binomial, all you have to do is exponentiate the x beta hat or to make adjusted predictions in the usual way. The negative binomial is estimating the log(E(y|x)), which is more appropriate for mean comparisons than the E(log(y|x)) that OLS on log(y is estimating.

Will

At 05:09 PM 3/25/2003 -0500, you wrote:

I am running a negative binomial model simulating the effect of changes in right-hand side variables on the predicted count of the outcome. There is a well documented transformation problem with log OLS models. Are there any transformation issues associated with analyzing predicted counts from the negative binomial model? If so, do you have any do files or concrete suggestions for handling this problem?

Thank you,

Maureen Stewart

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Willard G. Manning Professor Dept. of Health Studies -- MC 2007 The University of Chicago 5841 So. Maryland Ave. Chicago, IL 60637 Phone: 773-834-1971 (direct) 773-702-2453 (department) Fax: 773-702-1979 E-mail: w-manning@uchicago.edu * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: negative binomial model - transformation***From:*Maureen Stewart <mstewart@hsph.harvard.edu>

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