The Zero-Inflated Poisson (ZIP) Regression Model is used to analyze count
data with excess zeros. ZIP model are used to study over-dispersion count data
with an excess of zero counts.
Applications occur in healthcare sociology marketing research and so
on. In this paper we address a
typical problem of fitting over-dispersion data with standard Poisson model,
provide the methodology of calculating the parameters of ZIP model and
illustrate conceptual and computational features of ZIP model. Two examples are given to demonstrate
the usage of the ZIP model and both are implemented with R codes. After comparing the results generated by
the ZIP model with the results got from the standard Poisson model, we draw a
conclusion that ZIP model could be a better fit for over-dispersion data.