Zero-inflated models are commonly used in the analysis of count data, such as the number of visits a patient makes to their dentist in one year. Count data can take non-negative integer values 0, 1, 2, … .
For statistical analysis, the distribution of the counts is often represented using a Poisson or Negative Binomial distributions.
This research aims to study the literature of the Zero-inflated Regression Models and potential further expansion for count data modelling in health science/industry.