Zero-Inflated Poisson Regression Models with Right Censored Count Data

A Poisson model typically is assumed for count data. However Poisson model is not suitable for data because of too many zeros. Furthermore, the response variable in such cases is censored for some values. In this paper, a zero-inflated Poisson regression model is introduced on censored data. 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 in terms of parameters estimation and their standard errors via simulation and an example.