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st: Re censored negative binomial; Long/Freese book |

Date |
Sun, 4 Dec 2005 12:49:45 EST |

StataListers: Kit has posted posted a program that I submitted called censornb to the SSC site. The program is a maximum likelihood censored negative binomial regression procedure, parameterized as a survival model. In this respect it is similar to the cpoisson program -- censored Poisson -- that is already on the site. There are two parameterizations of censored count models. The traditonal econometric parameterization requires the user to specify cut points, beyond which observations are considered censored. For instance, given a range of counts from 0-50, one can specify a cut point at 5 to indicate left censoring of observations less than 5. Those outlying observations are then re-valued to that of the cut point. The same is the case for upper or right censoring. Observations within the cut points cannot be censored. I have called the above an econometric parameterization. It differs from the traditional survival model parameterization where any observation in the data may be identified as right or left censored. Moreover, the values of censored survival observations are not changed. This is the parameterization used for Cox proportional hazard models, as well as the standard parametric survival models, e.g. exponential, Weibull, lognormmal, gamma, and so forth. It took me awhile to figure out the loglikelihood functions for right and left censored negative binomial observations, which employs an incomplete beta function. There is no other software with which to directly compare results, nor is there any literature on parameterization. I used LIMDEP's censored Poisson and censored NB programs, with a specified cut point, to compare with the survival censored Poisson and censored NB programs. I defined censored observations to be the same as those above the cut point I selected in LIMDEP. So the same block of observations were censored, The results, as would be expected, were nearly identical. The advantage, however, with the survival version is that there is no limitation on which observations can be left or right censored in the same model. I have also added the AIC and BIC GOF statistics to facilitate model comparson. The program is written using version 9.1, hence allowing for a variety of ML and survey options. I wish to recommend the recently published 2nd edition of Long/Freese's Stata Press book - "Regression Models for Categorical Dependent Variables Using Stata". Many of the discussions are the same as those in their 2003 revised 1st edition. But there is also a substantial amount of added material, all referencing Stata 9 programs and code. It's a whopping 527 pages in length compared with the previous 368 pages. I believe the book to be indespensible for any Stata user who deals with categorical response data, such as logistic regression, Poisson and negative boinomial regression, and ordinal and multinomial models. There is a great discussion of ZIP/ZINB and an added section on hurdle models, which are not in official Stata. I might add here that unbeknownst to the authors, there are 9 hurdle models posted to the SSC site. These may be used in conjunction with the book for modeling count data for which the 0 counts are thought to have come from a separate process than the process generating positive counts. Anyhow, I believe the book to be one of the most useful books on discrete response data currently on the market. A worthwhile purchase! Joe Hilbe * * 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/

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