Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease
For count data, though a zero-inflated model can work perfectly well with an excess of zeroes and the generalized Poisson model can tackle over- or under-dispersion, most models cannot simultaneously deal with both zero-inflated or zero-deflated data and over- or under-dispersion. Ear diseases are i...
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doaj-05c523e5909746f289765193097dcf572021-09-26T00:07:04ZengMDPI AGEntropy1099-43002021-09-01231206120610.3390/e23091206Generalized Poisson Hurdle Model for Count Data and Its Application in Ear DiseaseGuoxin Zuo0Kang Fu1Xianhua Dai2Liwei Zhang3School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, ChinaSchool of Mathematics and Statistics, Central China Normal University, Wuhan 430079, ChinaSchool of Public Administration, Central China Normal University, Wuhan 430079, ChinaSchool of Mathematics and Statistics, Central China Normal University, Wuhan 430079, ChinaFor count data, though a zero-inflated model can work perfectly well with an excess of zeroes and the generalized Poisson model can tackle over- or under-dispersion, most models cannot simultaneously deal with both zero-inflated or zero-deflated data and over- or under-dispersion. Ear diseases are important in healthcare, and falls into this kind of count data. This paper introduces a generalized Poisson Hurdle model that work with count data of both too many/few zeroes and a sample variance not equal to the mean. To estimate parameters, we use the generalized method of moments. In addition, the asymptotic normality and efficiency of these estimators are established. Moreover, this model is applied to ear disease using data gained from the New South Wales Health Research Council in 1990. This model performs better than both the generalized Poisson model and the Hurdle model.https://www.mdpi.com/1099-4300/23/9/1206over-dispersion and under-dispersionexcess of zerogeneralized Poisson regressionHurdle modelgeneralized Poisson Hurdle modelgeneralized method of moments |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Guoxin Zuo Kang Fu Xianhua Dai Liwei Zhang |
spellingShingle |
Guoxin Zuo Kang Fu Xianhua Dai Liwei Zhang Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease Entropy over-dispersion and under-dispersion excess of zero generalized Poisson regression Hurdle model generalized Poisson Hurdle model generalized method of moments |
author_facet |
Guoxin Zuo Kang Fu Xianhua Dai Liwei Zhang |
author_sort |
Guoxin Zuo |
title |
Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease |
title_short |
Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease |
title_full |
Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease |
title_fullStr |
Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease |
title_full_unstemmed |
Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease |
title_sort |
generalized poisson hurdle model for count data and its application in ear disease |
publisher |
MDPI AG |
series |
Entropy |
issn |
1099-4300 |
publishDate |
2021-09-01 |
description |
For count data, though a zero-inflated model can work perfectly well with an excess of zeroes and the generalized Poisson model can tackle over- or under-dispersion, most models cannot simultaneously deal with both zero-inflated or zero-deflated data and over- or under-dispersion. Ear diseases are important in healthcare, and falls into this kind of count data. This paper introduces a generalized Poisson Hurdle model that work with count data of both too many/few zeroes and a sample variance not equal to the mean. To estimate parameters, we use the generalized method of moments. In addition, the asymptotic normality and efficiency of these estimators are established. Moreover, this model is applied to ear disease using data gained from the New South Wales Health Research Council in 1990. This model performs better than both the generalized Poisson model and the Hurdle model. |
topic |
over-dispersion and under-dispersion excess of zero generalized Poisson regression Hurdle model generalized Poisson Hurdle model generalized method of moments |
url |
https://www.mdpi.com/1099-4300/23/9/1206 |
work_keys_str_mv |
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1717366996848345088 |