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Generalized Poisson Hurdle Model for Count Data and Its Application in Ear Disease
Authors:Guoxin Zuo  Kang Fu  Xianhua Dai  Liwei Zhang
Affiliation:1.School of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China; (G.Z.); (K.F.); (L.Z.);2.School of Public Administration, Central China Normal University, Wuhan 430079, China;3.Center for Labor and Social Security Research, Central China Normal University, Wuhan 430079, China
Abstract:
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.
Keywords:over-dispersion and under-dispersion   excess of zero   generalized Poisson regression   Hurdle model   generalized Poisson Hurdle model   generalized method of moments
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