Hurdle negative binomial regression model with right censored count data

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Document typeArticle
Defense date2012
PublisherInstitut d'Estadística de Catalunya
Rights accessOpen Access
Abstract
A Poisson model typically is assumed for count data. In many cases because of many zeros in
the response variable, the mean is not equal to the variance value of the dependent variable.
Therefore, the Poisson model is no longer suitable for this kind of data. Thus, we suggest
using a hurdle negative binomial regression model to overcome the problem of overdispersion.
Furthermore, the response variable in such cases is censored for some values. In this paper,
a censored hurdle negative binomial regression model is introduced on count data with many
zeros. The estimation of regression parameters using maximum likelihood is discussed and the
goodness-of-fit for the regression model is examined
CitationSaffari, Seyed Ehsan; Adnan, Robiah; Greene, William. Hurdle negative binomial regression model with right censored count data. "SORT", vol. 36, núm. 2, p. 181-194.
ISSN1696-2281
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