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From |
David Airey <david.airey@vanderbilt.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Exact Poisson Regression |

Date |
Sun, 17 Feb 2008 10:45:01 -0600 |

.

I read your review of Stata 9 and of exact statistics in various packages. Both were good reads. Thank you!

-Dave

On Feb 16, 2008, at 9:14 AM, Jhilbe@aol.com wrote:

Gary Anderson asks about whether anyone has developed an exact negative

binomial

command. No one has done that yet, but the folks at Cytel talked to me about

it back

in November 2005 when I gave an ASA LearnStat course in the Boston area.

The parameterization of the exact negative binomial would take the canonical

form; ie

it would not be the Poisson-gamma mixture model parameterization with which

most

statisticians are familiar. Therefore, it would not have the same

relationship to Poisson

overdispersion as does the NB-2 type of negative binomial, which is

estimated by using

the default form of -nbreg-. The canonical negative binomial can be used to

model count

data, and does a good job modeling data that is Poisson- overdispersed. I say

this because

negative binomial models can be overdispersed as well. But, because it does

not have

the log link as does Poisson (and NB-2), the canonical NB heterogeneity or

ancillary parameter

it cannot be used for direct comparisons with Poisson overdispersion as is

NB-2. Again, an exact NB

would be a canonical NB.

I submitted a maximum likelihood canonical NB Stata program to SSC last year

called -cnbreg-.

It has all of the bells and whistles as the usual Stata maximum likelihood

commands. I've been doing simulation studies on the NB-C model, as I call the

canonical NB in "Negative Binomial Regression", comparing it with Poisson,

NB-2, and NB-1 models. I intend to publish the results when completed.

NB-C is actually a nice model and can do a better job modeling some types of

data than NB-2 or NB-1.

I think it is worth the effort to construct an exact NB command, but I now

doubt that Cytel will get to it.

LogXact, Cytel's software application for modeling exact logistic and exact

Poisson models, is not alone any more in providing this capability to its

users. SAS and SPSS can model exact logistic models, and Stata both exact

logistic and exact Poisson. Because of the strong competition in this regard, it is

my understanding that Cytel is emphasizing development of packages such as

East, which is marketed to the clinical trials industry. I doubt that it will

develop an exact NB now. And since there are no published algorithms showing

how to do it, I very much doubt that SAS or SPSS will take it on. That leaves

Stata Corp. An exact NB, although of canonical parameterization, still would

be valuable for modeling counts with excessive correlation in the data. There

are great reasons why I think it worth the effort.

By the way, Bob Oster and I wrote an article for "The American Statistician"

(current issue) which compares the exact statistics capabilities of

StatXact/LogXact, SAS, SPSS, and Stata. Those of you who have an interest in exact

statistics may find the review to be helpful.

Joseph Hilbe

**************The year's hottest artists on the red carpet at the Grammy

Awards. Go to AOL Music.

(http://music.aol.com/grammys?NCID=aolcmp00300000002565)

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-- David C. Airey, Ph.D. Pharmacology Research Assistant Professor Center for Human Genetics Research Member Department of Pharmacology School of Medicine Vanderbilt University Rm 8158A Bldg MR3 465 21st Avenue South Nashville, TN 37232-8548 TEL (615) 936-1510 FAX (615) 936-3747 EMAIL david.airey@vanderbilt.edu URL http://people.vanderbilt.edu/~david.c.airey/dca_cv.pdf URL http://www.vanderbilt.edu/pharmacology * * 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: RE: Exact Poisson Regression***From:*Jhilbe@aol.com

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