Parameter estimation on hurdle poisson regression model with censored data

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 same as before. In fact, the variance value of the dependent variable will be muc...

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Main Authors: Saffari, S., Adnan, R., Greene, William
Format: Journal Article
Published: 2012
Online Access:http://hdl.handle.net/20.500.11937/53459
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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 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 same as before. In fact, the variance value of the dependent variable will be much more than the mean value of the dependent variable and this is called over-dispersion. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, it is suggested to use a hurdle Poisson regression model to overcome over-dispersion problem. Furthermore, the response variable in such cases is censored for some values. In this paper, a censored hurdle Poisson regression model is introduced on count data with many zeros. In this model, we consider a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness-of-fit for the regression model is examined. We study the effects of right censoring on estimated parameters and their standard errors via an example.
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spelling curtin-20.500.11937-534592017-09-13T16:11:53Z Parameter estimation on hurdle poisson regression model with censored data Saffari, S. Adnan, R. Greene, William 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 same as before. In fact, the variance value of the dependent variable will be much more than the mean value of the dependent variable and this is called over-dispersion. Therefore, Poisson model is not suitable anymore for this kind of data because of too many zeros. Thus, it is suggested to use a hurdle Poisson regression model to overcome over-dispersion problem. Furthermore, the response variable in such cases is censored for some values. In this paper, a censored hurdle Poisson regression model is introduced on count data with many zeros. In this model, we consider a response variable and one or more than one explanatory variables. The estimation of regression parameters using the maximum likelihood method is discussed and the goodness-of-fit for the regression model is examined. We study the effects of right censoring on estimated parameters and their standard errors via an example. 2012 Journal Article http://hdl.handle.net/20.500.11937/53459 10.11113/jt.v57.1533 restricted
spellingShingle Saffari, S.
Adnan, R.
Greene, William
Parameter estimation on hurdle poisson regression model with censored data
title Parameter estimation on hurdle poisson regression model with censored data
title_full Parameter estimation on hurdle poisson regression model with censored data
title_fullStr Parameter estimation on hurdle poisson regression model with censored data
title_full_unstemmed Parameter estimation on hurdle poisson regression model with censored data
title_short Parameter estimation on hurdle poisson regression model with censored data
title_sort parameter estimation on hurdle poisson regression model with censored data
url http://hdl.handle.net/20.500.11937/53459