Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data

Typically, a Poisson model is assumed for count data. In many cases, there are many zeros in the dependent variable, thus the mean is not equal to the variance value of the dependent variable. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, we...

Full description

Bibliographic Details
Main Authors: Saffari, S., Adnan, R., Greene, William
Format: Journal Article
Published: Wiley-Blackwell Publishing Ltd 2013
Online Access:http://hdl.handle.net/20.500.11937/53150
_version_ 1848759076901617664
author Saffari, S.
Adnan, R.
Greene, William
author_facet Saffari, S.
Adnan, R.
Greene, William
author_sort Saffari, S.
building Curtin Institutional Repository
collection Online Access
description Typically, a Poisson model is assumed for count data. In many cases, there are many zeros in the dependent variable, thus the mean is not equal to the variance value of the dependent variable. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, we suggest using a hurdle-generalized Poisson regression model. Furthermore, the response variable in such cases is censored for some values because of some big values. A censored hurdle-generalized Poisson regression model is introduced on count data with many zeros in this paper. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness-of-fit for the regression model is examined. An example and a simulation will be used to illustrate the effects of right censoring on the parameter estimation and their standard errors.
first_indexed 2025-11-14T09:54:08Z
format Journal Article
id curtin-20.500.11937-53150
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:54:08Z
publishDate 2013
publisher Wiley-Blackwell Publishing Ltd
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-531502017-10-12T07:07:02Z Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data Saffari, S. Adnan, R. Greene, William Typically, a Poisson model is assumed for count data. In many cases, there are many zeros in the dependent variable, thus the mean is not equal to the variance value of the dependent variable. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, we suggest using a hurdle-generalized Poisson regression model. Furthermore, the response variable in such cases is censored for some values because of some big values. A censored hurdle-generalized Poisson regression model is introduced on count data with many zeros in this paper. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness-of-fit for the regression model is examined. An example and a simulation will be used to illustrate the effects of right censoring on the parameter estimation and their standard errors. 2013 Journal Article http://hdl.handle.net/20.500.11937/53150 10.1111/j.1467-9574.2012.00532.x Wiley-Blackwell Publishing Ltd restricted
spellingShingle Saffari, S.
Adnan, R.
Greene, William
Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data
title Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data
title_full Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data
title_fullStr Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data
title_full_unstemmed Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data
title_short Investigating the impact of excess zeros on hurdle-generalized Poisson regression model with right censored count data
title_sort investigating the impact of excess zeros on hurdle-generalized poisson regression model with right censored count data
url http://hdl.handle.net/20.500.11937/53150