@article{(Open Science Index):https://publications.waset.org/pdf/16176,
	  title     = {Zero Inflated Models for Overdispersed Count Data},
	  author    = {Y. N. Phang and  E. F. Loh},
	  country	= {},
	  institution	= {},
	  abstract     = {The zero inflated models are usually used in modeling
count data with excess zeros where the existence of the excess zeros
could be structural zeros or zeros which occur by chance. These type
of data are commonly found in various disciplines such as finance,
insurance, biomedical, econometrical, ecology, and health sciences
which involve sex and health dental epidemiology. The most popular
zero inflated models used by many researchers are zero inflated
Poisson and zero inflated negative binomial models. In addition, zero
inflated generalized Poisson and zero inflated double Poisson models
are also discussed and found in some literature. Recently zero
inflated inverse trinomial model and zero inflated strict arcsine
models are advocated and proven to serve as alternative models in
modeling overdispersed count data caused by excessive zeros and
unobserved heterogeneity. The purpose of this paper is to review
some related literature and provide a variety of examples from
different disciplines in the application of zero inflated models.
Different model selection methods used in model comparison are
	    journal   = {International Journal of Health and Medical Engineering},
	  volume    = {7},
	  number    = {8},
	  year      = {2013},
	  pages     = {1331 - 1333},
	  ee        = {https://publications.waset.org/pdf/16176},
	  url   	= {https://publications.waset.org/vol/80},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 80, 2013},