Hurdle negative binomial regression model with right censored count data
Access Status
Authors
Date
2012Type
Metadata
Show full item recordAbstract
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 goodnessoffit for the regression model is examined.
Citation
Source Title
Additional URLs
Department
Collections
Related items
Showing items related by title, author, creator and subject.

Saffari, S.; Adnan, R.; Greene, William (2012)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 ...

Saffari, S.; Adnan, R.; Greene, William; Ahmad, M. (2013)Typically, a Poisson regression model is assumed for count data. In many cases, there are many zeros in the dependent variable, therefore the mean is not equal to the variance value of the dependent variable. Thus, we ...

Greene, William; Saffari, S.E.; Adnan, R. (2012)A Poisson model typically is assumed for count data. In many cases, there are many zeros in the dependent variable and because of these many zeros, the mean and the variance values of the dependent variable are not the ...