In many situations count data have a large proportion of zeros and the zero-inflated Poisson
regression (ZIP) model may be appropriate. A simple score test for zero-inflation, comparing …

When analyzing Poisson count data sometimes a high frequency of extra zeros is observed.
The Zero‐Inflated Poisson (ZIP) model is a popular approach to handle zero‐inflation. In this …

Count data often show a higher incidence of zero counts than would be expected if the data
were Poisson distributed. Zero‐inflated Poisson regression models are a useful class of …

In a 1992 Technometrics paper, Lambert (1992, 34, 1–14) described zero‐inflated Poisson
(ZIP) regression, a class of models for count data with excess zeros. In a ZIP model, a count …

In certain applications involving count data, it is sometimes found that zeros are observed
with a frequency significantly higher (lower) than predicted by the assumed model …

For count data, typically, a Poisson model is assumed. However, it has been observed in
various applications that this model does not fit, because of too few or too many zeros in the …

Count data with excess zeros relative to a Poisson distribution are common in many
biomedical applications. A popular approach to the analysis of such data is to use a zero …

A Score Test for Zero Inflation in a Poisson Distribution Page 1 BIOMETRICS 51, 738-743 June
1995 A Score Test for Zero Inflation in a Poisson Distribution Jan van den Broek Center for …

Zero‐inflated Poisson regression is a popular tool used to analyze data with excessive
zeros. Although much work has already been performed to fit zero‐inflated data, most …

The negative binomial (NB) model and the generalized Poisson (GP) model are common
alternatives to Poisson models when overdispersion is present in the data. Having …